{"id":"W6967941400","doi":"10.5281/zenodo.15270517","title":"RecGaze Dataset - Public Version","year":2025,"lang":"en","type":"dataset","venue":"Radboud Repository (Radboud University)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"European Commission","keywords":"Cursor (databases); Selection (genetic algorithm); Eye tracking; Download; User interface","routes":{"ca_aff":true,"ca_fund":false,"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","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.0006601473,0.00173728,0.001682792,0.00653662,0.002152186,0.001113714,0.005349927,0.002159814,0.0003898315],"category_scores_gemma":[0.0003172975,0.002104544,0.0006304304,0.00536896,0.0009558747,0.001519016,0.002711211,0.002796998,0.00199105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003595491,"about_ca_system_score_gemma":0.00283534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002169121,"about_ca_topic_score_gemma":0.00008708997,"domain_scores_codex":[0.9906272,0.001652322,0.001036088,0.002977997,0.001869994,0.001836455],"domain_scores_gemma":[0.9903975,0.0005222432,0.001394207,0.005981561,0.0006366879,0.001067862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004142657,0.0006852098,0.00003551837,0.0003900484,0.0008978716,0.005676856,0.00001369709,0.0001626502,0.0001833781,0.001062947,0.9904353,0.00004228121],"study_design_scores_gemma":[0.002104241,0.0001973363,0.00002824432,0.0003926057,0.001639896,0.0002458259,0.0002039088,0.00009248478,0.00006349984,0.00000546004,0.9931067,0.00191981],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008712825,0.001285509,0.00002246121,0.0001671923,0.008667526,0.001166077,0.9707623,0.0007153077,0.01712654],"genre_scores_gemma":[0.00002267382,0.00102455,0.00008599529,0.0001150183,0.0009127496,0.000006677005,0.9319856,0.000115278,0.06573151],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04860497,"threshold_uncertainty_score":0.9999232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01208400768916103,"score_gpt":0.2154356074467579,"score_spread":0.2033515997575968,"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."}}