{"id":"W4409977813","doi":"10.2196/70853","title":"Misrepresentation of Overall and By-Gender Mortality Causes in Film Using Online, Crowd-Sourced Data: Quantitative Analysis","year":2025,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Mental Health via Writing","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Misrepresentation; Computer science; Political science; World Wide Web; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005570696,0.0003208774,0.000275282,0.004045314,0.0006248656,0.001172432,0.00045893,0.0004051495,0.001375081],"category_scores_gemma":[0.0265912,0.0001271053,0.0003404727,0.002180606,0.000765157,0.00113058,0.001412371,0.000409102,0.0004305037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007080936,"about_ca_system_score_gemma":0.0003186065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004871618,"about_ca_topic_score_gemma":0.005236179,"domain_scores_codex":[0.995514,0.00181923,0.0004342134,0.0008138319,0.001189521,0.0002292643],"domain_scores_gemma":[0.9734676,0.01437821,0.005423684,0.001765263,0.00453631,0.0004290205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003868012,0.0001708772,0.9145606,0.0005685703,0.0002057231,0.000271733,0.02127242,0.001199642,0.007314886,0.001369322,0.007158945,0.04552045],"study_design_scores_gemma":[0.00001132301,0.0001349524,0.9560983,0.0001593744,0.00005728435,0.0002587684,0.02075257,0.009254664,0.004124345,0.000747201,0.008342463,0.00005865153],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851366,0.0001583782,0.003490136,0.0002160489,0.00004539411,0.0002456668,0.007653717,0.00004738814,0.003006547],"genre_scores_gemma":[0.9874765,0.00009383986,0.004292078,0.0001165855,0.0000761886,0.0004360188,0.006614112,0.000021913,0.0008727768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005570696,"threshold_uncertainty_score":0.02946103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3881076233440315,"score_gpt":0.6099597082243308,"score_spread":0.2218520848802993,"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."}}