{"id":"W4413580735","doi":"10.1101/2025.08.20.671334","title":"Gaze-related functions driving gaze anchoring in reaching","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Deutsche Forschungsgemeinschaft","keywords":"Gaze; Anchoring; Psychology; Cognitive psychology; Computer science; Computer vision; Communication; Cognitive science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001139199,0.0006615891,0.0007413473,0.00131387,0.0003111663,0.000417908,0.002090223,0.0008797102,0.00001016504],"category_scores_gemma":[0.0004897454,0.0007769403,0.0002033953,0.001935985,0.0001234795,0.0003905078,0.001979785,0.002613404,0.00006844105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006690235,"about_ca_system_score_gemma":0.0006508535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001307878,"about_ca_topic_score_gemma":0.0000187914,"domain_scores_codex":[0.9958277,0.0002493914,0.0008492706,0.001785503,0.0003706147,0.000917515],"domain_scores_gemma":[0.9965185,0.0001927119,0.000439858,0.002380032,0.0002865643,0.0001823219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002801891,0.001387751,0.3074328,0.001416389,0.000948346,0.001082056,0.0002630787,0.01005792,0.5234111,0.1511624,0.001946263,0.0008638515],"study_design_scores_gemma":[0.001974269,0.0001317889,0.855379,0.008326819,0.000203519,1.913334e-7,0.00001747403,0.05248047,0.06795645,0.0002777193,0.009459313,0.003792971],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6700351,0.001726262,0.3154952,0.001308374,0.005651477,0.000841492,0.00005220173,0.004584818,0.0003050248],"genre_scores_gemma":[0.972943,0.0001066733,0.02643388,0.00008484573,0.0001603823,0.0001723453,2.156308e-7,0.00005397778,0.00004465166],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5479462,"threshold_uncertainty_score":0.9996876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01272955978555008,"score_gpt":0.2228568784947802,"score_spread":0.2101273187092301,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}