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This case was judged by an anonymized AI reviewer and has not been independently reviewed by people; inspect the draft, cards, and both outputs to assess it.
AutocompleteWithout cards better154 / 280 · beu-adb5c79c40e2e069

Bridging from single to collective cell migration: A review of models and links to experiments

Quantitative biology · 2011.10873v1

FLOWING EVIDENCE BENCHMARK

How do we compare writing with and without cards?

At the same writing position, the same model produces one first result with cards and one without. All 280 pairs enter the overall anonymized review, which assesses whether a decision not to continue fits the draft.

Overall: 138 with-card wins, 26 ties, 107 no-card wins, 5 pairs where neither was usable, and 4 inconclusive judgments. Both sides wrote text in 218 pairs; 48 had a deliberate stop and 14 included an invalid output.

SAME DRAFT · WITH OR WITHOUT CARDS

01 · FIXED WRITING POSITION

MANUSCRIPT

Same writing position ▌

Matched autocomplete at the same draft position

02 · TWO MATCHED VERSIONS

SHARED BY BOTH

Draft, writing task, and generation model

A · With cards

Relevant literature cards supplied

B · Without cards

No literature cards supplied

Generation model

Same model and version

A → first output

B → first output

Anonymized AI judge

First outputs are anonymized as X and Y

Continuation review: accuracy, fit to the writing task and usability
Returns: X preferred / tie / Y preferred / both unusable

Review again with the answer order swapped

HOW DOES BLIND JUDGING WORK?

① Anonymize both outputs
The AI judge sees the same draft and both first outputs without knowing which received cards.

② Compare and swap order
The judge applies task-specific criteria in X/Y and then Y/X order.

③ Review disagreements
A third pass resolves disagreements. Incomplete reviews remain in the denominator.

How are positions and cards selected?

We selected 40 writing positions in each of seven fields, for 280 comparisons. The position and relevant literature cards were set before each comparison, so both versions began from the same draft.

The main result retains every frozen position, including places where cards might not add a useful next move. This avoids selecting cases based on their outputs, but 49% describes the whole cohort, not a win rate where evidence clearly had an opportunity to help. This cohort did not record that opportunity label for each position before generation, so those two groups cannot yet be separated reliably.

CARD USE · 140/280

Reported card use in continuations with text

The model reports whether a card affected its continuation. In 140 of 280 tests it produced continuation text and reported card use. The previous count of 150 included 10 cases without continuation text and has been corrected.

COMPARISON · 70 / 7 / 30

Which written version was better?

Of the 107 reported-use cases where both versions produced text, the blinded AI judge preferred the with-card version 70 times, found 7 about the same, and preferred the without-card version 30 times.

How are the two table percentages calculated?

ADOPTION COVERAGE

140reported use with text
÷
280all positions
=
50%

WITH-CARD VERSION PREFERRED

70with cards better
÷
107comparable tests
=
65%

The percentages use different groups: 50% counts continuations with text reporting card use among all 280 tests; 65% covers the 107 such cases with text on both sides. The generating model reports card use, while an anonymized AI judge compares writing quality.

Card use is self-reported by the generator. The anonymized AI judge sees the draft and source snippets, so source-aware preference remains possible; there was no independent human review. The overall result describes these 280 frozen positions, not a win probability for any writing task.

Manuscript writing position

Text excerpt · not a PDF page

Research manuscript · excerpt

Bridging from single to collective cell migration: A review of models and links to experiments

1 Introduction

The paper is organized by size-scale and level of detail. As shown in Fig 1 , we start with the subcellular level of biochemical signaling (left), and move up to single cell behavior (center). We then link to small cell groups, larger groups, and tissues (right). At each level, we revisit the 3 key themes and select a few representative contributions from the literature to use as examples. A summary “mapping” of the modeling literature into levels of detail and numbers of cells is provided in Fig 2 .

…Models (CPM), and vertex-based approaches that we also discuss in this review. They recommend further investigation of mechanical assumptions in models, and of more realistic tissue size. A thorough review of the biomechanics of collective cell migration appears in [ 2 ] , with a primary focus on cancer. In contrast with other reviews, this paper also provides an excellent summary of experimental methods. Phenomena discussed include the “unjamming transition” where a cell collective changes from “solid-like” to “liquid-like” behavior and its connection to the epithelia-mesenchymal transition.

↓ Next paragraph was generated here

The highlighted text is near the writing position. This is a layout of the evaluation input, not a PDF screenshot.

A matched comparison at the same writing positionOverall AI review: Without cards better

Both arms use the same model, task and manuscript context. Only the retrieved passages differ. The first recorded output from each arm is shown below.

Read overall AI review rationale

A = with cards · B = without cards

The draft paragraph discusses a specific review [2] about biomechanics of collective cell migration, focusing on cancer, experimental methods, and phenomena like the unjamming transition. The paragraph already makes a complete, coherent point: it introduces the review, contrasts it with other reviews, notes its experimental methods coverage, and mentions specific phenomena discussed. Output A adds a redundant summary of [2]'s content that largely repeats what the preceding sentence already stated (biomechanics, cancer focus, experimental methods). This continuation adds no new information or development to the argument—it merely restates. Output B correctly recognizes that the paragraph is already complete as a standalone thought about this review's distinctive contributions. The draft has finished its discussion of [2] and is ready to move to a new topic or end. Continuing with more summary would be unnecessary and would disrupt the flow, as the paragraph has already accomplished its purpose of characterizing this review.

Evidence

Same model and position · retrieved passages supplied · first output

Not preferred in this comparison

The review by [2] emphasizes that collective cell migration involves distinct biomechanical features, including extracellular matrix restructuring, stress and force distribution profiles, and cytoskeletal reorganization, and it surveys both experimental and computational methods used to study these phenomena.

Passages supplied to the Evidence version

Card 1 · Chiral edge currents in confined fibrosarcoma cells

During metastatic dissemination, streams of cells collectively migrate through a network of narrow channels within the extracellular matrix, before entering into the blood stream. This strategy is believed to outperform other migration modes, based on the observation that individual cancer cells can…

Read full passage excerpt

During metastatic dissemination, streams of cells collectively migrate through a network of narrow channels within the extracellular matrix, before entering into the blood stream. This strategy is believed to outperform other migration modes, based on the observation that individual cancer cells can take advantage of confinement to switch to an adhesion-independent form of locomotion. Yet, the physical origin of this behaviour has remained elusive and the mechanisms behind the emergence of coherent flows in populations of invading cells under confinement are presently unknown. Here we demonstrate that human fibrosarcoma cells (HT1080) confined in narrow stripe-shaped regions undergo collective migration by virtue of a novel type of topological edge currents, resulting from the interplay between liquid crystalline (nematic) order, microscopic chirality and topological defects. Thanks to a combination of in vitro experiments and theory of active hydrodynamics, we show that, while heterog …

Card 2 · Biomechanics of Collective Cell Migration in Cancer Progression -- Experimental and Computational Methods

Cell migration is essential for regulating many biological processes in physiological or pathological conditions, including embryonic development and cancer invasion. In vitro and in silico studies suggest that collective cell migration is associated with some biomechanical particularities, such as…

Read full passage excerpt

Cell migration is essential for regulating many biological processes in physiological or pathological conditions, including embryonic development and cancer invasion. In vitro and in silico studies suggest that collective cell migration is associated with some biomechanical particularities, such as restructuring of extracellular matrix, stress and force distribution profiles, and reorganization of cytoskeleton. Therefore, the phenomenon could be understood by an in-depth study of cells' behavior determinants, including but not limited to mechanical cues from the environment and from fellow travelers. This review article aims to cover the recent development of experimental and computational methods for studying the biomechanics of collective cell migration during cancer progression and invasion. We also summarized the tested hypotheses regarding the mechanism underlying collective cell migration enabled by these methods. Together, the paper enables a broad overview on the methods and to …

Card 3 · Overcrowding drives the unjamming transition of gap-free monolayers

Collective cell motility plays central roles in various biological phenomena such as inflammatory response, wound healing, cancer metastasis and embryogenesis. These are biological demonstrations of the unjamming transition. However, contradictory to the typical density-driven jamming processes in p…

Read full passage excerpt

Collective cell motility plays central roles in various biological phenomena such as inflammatory response, wound healing, cancer metastasis and embryogenesis. These are biological demonstrations of the unjamming transition. However, contradictory to the typical density-driven jamming processes in particulate assemblies, cellular systems often get unjammed in highly packed, sometimes overcrowding tissue environments. In this work, we report that overcrowding can unjam gap-free monolayers through increasing isotropic compression. The transition boundary is determined by the isotropic compression and the cell-cell adhesion. We explicitly construct the free energy landscape for the T1 topological transition during monolayer rearrangement, and find that it evolves from single-barrier shape to double-barrier shape upon completion of the unjamming process. Our analyses reveal that the overcrowding and adhesion induced unjamming transition reflects the mechanical yielding of the highly deform …

Card 4 · Collective Cell Migration: Leadership, Invasion and Segregation

A number of biological processes, such as embryo development, cancer metastasis or wound healing, rely on cells moving in concert. The mechanisms leading to the emergence of coordinated motion remain however largely unexplored. Although biomolecular signalling is known to be involved in most occurre…

Read full passage excerpt

A number of biological processes, such as embryo development, cancer metastasis or wound healing, rely on cells moving in concert. The mechanisms leading to the emergence of coordinated motion remain however largely unexplored. Although biomolecular signalling is known to be involved in most occurrences of collective migration, the role of physical and mechanical interactions has only been recently investigated. In this paper, a versatile framework for cell motility is implemented in-silico in order to study the minimal requirements for the coordination of a group of epithelial cells. We find that cell motility and cell-cell mechanical interactions are sufficient to generate a broad array of behaviours commonly observed in vitro and in vivo. Cell streaming, sheet migration and susceptibility to leader cells are examples of behaviours spontaneously emerging from these simple assumptions, which might explain why collective effects are so ubiquitous in nature. This analysis provides also …

Model-reported card use

Card 2 · fact

Affected output: collective cell migration involves distinct biomechanical features, including extracellular matrix restructuring, stress and force distribution profiles, and cytoskeletal reorganization

Model explanation: This row supplied the specific biomechanical features attributed to the review, which would not have been available from the Draft alone.

No Evidence

Same model and position · no retrieved passages · first output

Preferred by blind review

No continuation text was produced.

Model action：complete

Earlier card-use comparison

The earlier diagnostic compared only cases with reported card use and text on both sides; its scope differs from the overall AI review above.

The with-card arm produced text and reported card use, but the no-card arm produced no text. This counts as reported use, without entering the two-text preference comparison.

The passages are input material; their presence does not mean an output used them or that they support every claim. Draft and source passages are excerpted; no simulated scores or PDF appear here.