{"id":"W4390641816","doi":"10.4000/communication.18336","title":"Anne CRÉMIEUX et Ariane HUDELET (2020), La sérialité à l’écran. Comprendre les séries anglophones","year":2023,"lang":"fr","type":"article","venue":"Communication","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science","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":[0.0007471841,0.0003111837,0.00009342551,0.0005845022,0.003002688,0.003478778,0.0002731658,0.001114851,0.009228869],"category_scores_gemma":[0.002314108,0.0001451507,0.00009836018,0.0005681788,0.002787778,0.002726685,0.0009859909,0.001638153,0.001277433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00264369,"about_ca_system_score_gemma":0.001392117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03707115,"about_ca_topic_score_gemma":0.09015245,"domain_scores_codex":[0.9995474,0.0001987136,0.0000116449,0.00007847138,0.0001029642,0.0000607964],"domain_scores_gemma":[0.9995496,0.0002496286,0.00005696352,0.00001957656,0.00007047351,0.00005384035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001611769,0.0000235615,0.002787028,0.0002652442,0.00001244744,0.0008135081,0.1564374,0.00008812308,0.001224503,0.4162474,0.3029585,0.1189812],"study_design_scores_gemma":[0.000004126089,0.00001019929,0.002468058,0.0001809017,0.000002231799,0.0001582208,0.01020776,0.00001804384,0.0003262698,0.003218016,0.983401,0.000005245567],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.06022623,0.1274386,0.002505126,0.09517728,0.00821105,0.00005597394,0.000476976,0.0001008905,0.7058079],"genre_scores_gemma":[0.4598293,0.0234652,0.001361084,0.009656514,0.001972802,0.00007107383,0.0001883812,0.000141462,0.5033142],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03707115,"threshold_uncertainty_score":0.07371074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2585732281639851,"score_gpt":0.3515316774222338,"score_spread":0.0929584492582487,"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."}}