{"id":"W6936502520","doi":"10.58079/ncr6","title":"Monster(s) on screen(s)","year":2022,"lang":"en","type":"article","venue":"Industrias Culturais (Universidade de Coimbra)","topic":"Cinema and Media Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Process (computing); Work (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008548334,0.001012222,0.001063681,0.0007943367,0.001923398,0.005371682,0.001270808,0.002616846,0.8321196],"category_scores_gemma":[0.004493254,0.0004676197,0.0005711379,0.0007952236,0.0005852685,0.003682629,0.003973134,0.002348818,0.6783291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001276201,"about_ca_system_score_gemma":0.00133955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00506319,"about_ca_topic_score_gemma":0.01006792,"domain_scores_codex":[0.9992462,0.0001137587,0.0000371126,0.0001586203,0.0002635152,0.0001807948],"domain_scores_gemma":[0.9981889,0.0002177772,0.0001037159,0.0002475243,0.000595684,0.0006463388],"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":[0.00003317721,0.000006949606,0.00004458214,0.00004552774,0.000001264694,0.00005455227,0.00004944469,0.00001222899,0.0001872453,0.0006556661,0.9779367,0.02097265],"study_design_scores_gemma":[0.000001886526,0.000004021396,0.00008684713,0.0000153026,5.219547e-7,0.00003009178,0.00003855741,0.0000120424,0.00005077874,0.00004440144,0.9997131,0.000002386639],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.001104223,0.00340097,0.001349349,0.01353045,0.04285361,0.000196995,0.00288949,0.004702272,0.9299728],"genre_scores_gemma":[0.002561362,0.0005156139,0.0001693683,0.002053879,0.001779267,0.00004267384,0.0004014799,0.0005607062,0.9919156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8321196,"threshold_uncertainty_score":0.2394609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04873210507477086,"score_gpt":0.2261627893728099,"score_spread":0.1774306842980391,"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."}}