{"id":"W3124653913","doi":"10.2979/blackcamera.12.1.04","title":"On Tracking World Cinema: African Cinema at Film Festivals","year":2020,"lang":"en","type":"article","venue":"Black Camera","topic":"African history and culture studies","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Movie theater; Film industry; National cinema; Distribution (mathematics); State (computer science); Incentive; Colonialism; Media studies; Political science; History; Sociology; Art history; Law; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.004946436,0.0008902,0.0003295536,0.0048813,0.00903095,0.01118908,0.001399568,0.00339455,0.02517691],"category_scores_gemma":[0.01023738,0.000387654,0.0003395175,0.005593958,0.003880023,0.02103581,0.006232629,0.004114204,0.003977244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003586638,"about_ca_system_score_gemma":0.003190705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01530339,"about_ca_topic_score_gemma":0.02669078,"domain_scores_codex":[0.9971208,0.001484655,0.00008827489,0.0002708305,0.0005647812,0.0004706681],"domain_scores_gemma":[0.9943014,0.002958144,0.0004023227,0.0003051753,0.001229773,0.000803252],"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":[0.0000518236,0.00008380891,0.001497581,0.0007582658,0.000007080653,0.0002718582,0.04971568,0.0001030324,0.0009867483,0.09809836,0.534315,0.3141108],"study_design_scores_gemma":[0.000003806249,0.00001468743,0.001616478,0.001209818,0.000004506384,0.0001637786,0.01561415,0.00005177024,0.0001986995,0.003529872,0.9775799,0.00001261758],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02010171,0.1799704,0.01089429,0.1917049,0.02390902,0.0004619232,0.0005731101,0.0004437328,0.5719409],"genre_scores_gemma":[0.2812275,0.2895863,0.01504699,0.03633613,0.01910865,0.0008067991,0.001151401,0.001073995,0.3556623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02517691,"threshold_uncertainty_score":0.08422518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04224570640026939,"score_gpt":0.2855995826089643,"score_spread":0.2433538762086949,"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."}}