{"id":"W4408828093","doi":"10.1063/5.0263078","title":"Investigating the adoption of multimodel framework for identifying fake news","year":2025,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Data science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04103993,0.001043773,0.001339351,0.003247002,0.001377301,0.004567258,0.001716231,0.002041495,0.002685782],"category_scores_gemma":[0.1231344,0.0005946346,0.001653388,0.001962154,0.001063048,0.005523792,0.002157932,0.002345193,0.0002960356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00191616,"about_ca_system_score_gemma":0.002227252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01859636,"about_ca_topic_score_gemma":0.01480346,"domain_scores_codex":[0.9843938,0.0119007,0.0004230625,0.001796443,0.0008720857,0.0006139504],"domain_scores_gemma":[0.7183678,0.26077,0.007929409,0.006688344,0.005114322,0.001130175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001393431,0.001441675,0.3870919,0.0004682759,0.003499651,0.0009786132,0.003093883,0.2627158,0.001840771,0.1611186,0.003286892,0.1730706],"study_design_scores_gemma":[0.00003567798,0.0002262321,0.01585363,0.00005480176,0.0001996889,0.0001378316,0.0007661073,0.9450855,0.0005213036,0.03652031,0.000557766,0.00004118351],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.660574,0.0005559257,0.3311448,0.00234674,0.00007878441,0.0002176196,0.0004945425,0.0003231649,0.004264345],"genre_scores_gemma":[0.9659141,0.0001062621,0.03302424,0.00008312591,0.00002910879,0.00004751655,0.0002013573,0.0000182302,0.000575939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04103993,"threshold_uncertainty_score":0.2170425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1048963519800382,"score_gpt":0.3757447932827308,"score_spread":0.2708484413026926,"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."}}