{"id":"W7125581068","doi":"10.1109/ic-cgu67042.2025.11338001","title":"A Hybrid Model for Identifying Manipulated Videos using Advanced Computing Techniques","year":2025,"lang":"","type":"article","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Identification (biology); Feature (linguistics); Key (lock); Noise (video); Field (mathematics)","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":[0.0009220532,0.001019585,0.001210231,0.001724095,0.0006009283,0.002083306,0.001804655,0.001352586,0.002697534],"category_scores_gemma":[0.002729794,0.0004406621,0.001006194,0.001716698,0.0004917333,0.00250725,0.0009801207,0.001190291,0.001475289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008690059,"about_ca_system_score_gemma":0.001169935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01486603,"about_ca_topic_score_gemma":0.01225153,"domain_scores_codex":[0.9993981,0.0001108486,0.00004251862,0.0002089603,0.0001654239,0.00007409717],"domain_scores_gemma":[0.9986514,0.0005945071,0.0001117085,0.0001532101,0.0004312456,0.00005804795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007673718,0.0005963641,0.004416471,0.0002776451,0.0002773263,0.0002482886,0.0002281267,0.3941465,0.03168357,0.01341207,0.004258162,0.5496881],"study_design_scores_gemma":[0.000004804092,0.00004057357,0.0003123401,0.000004772233,0.00001801553,0.00002082959,0.00001299295,0.995728,0.001308345,0.002193003,0.0003481867,0.000008178982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02199502,0.0002808269,0.9750429,0.0001958781,0.00006010536,0.0001226174,0.0003029223,0.0009379327,0.001061853],"genre_scores_gemma":[0.4620349,0.000668409,0.5253155,0.0002058238,0.0001756646,0.0004956164,0.001307144,0.0002146833,0.009582414],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01486603,"threshold_uncertainty_score":0.02955902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05835604767402096,"score_gpt":0.3410214286014127,"score_spread":0.2826653809273917,"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."}}