{"id":"W4281485597","doi":"10.4000/culturemusees.8478","title":"Un tournant communicationnel pris à vitesse variable dans les musées de société au Québec","year":2022,"lang":"fr","type":"article","venue":"Culture & Musées","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science; Humanities; Art","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":[0.001640524,0.0002377647,0.0003217738,0.001593724,0.01848032,0.006611822,0.0009206052,0.0008738634,0.01524331],"category_scores_gemma":[0.003923312,0.0002484391,0.0001588409,0.002806117,0.007618654,0.002183923,0.003046033,0.001698522,0.0005466523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03857665,"about_ca_system_score_gemma":0.0408511,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.952548,"about_ca_topic_score_gemma":0.984168,"domain_scores_codex":[0.9987432,0.0003352363,0.00002774499,0.0002028227,0.0003035666,0.000387336],"domain_scores_gemma":[0.9969884,0.0005227846,0.0003372774,0.0001652934,0.001022612,0.0009636595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0002540755,0.0000620483,0.097375,0.0003906676,0.00009692978,0.002027748,0.5536678,0.000736603,0.004705263,0.1212317,0.05717688,0.1622753],"study_design_scores_gemma":[0.00001133443,0.00003765076,0.1855439,0.000492873,0.00005583286,0.0003573731,0.3179815,0.0006077457,0.0006213515,0.003573653,0.4906307,0.00008622134],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7631605,0.006168305,0.003438198,0.02437137,0.0003701668,0.00006066217,0.0009042613,0.0001349755,0.2013915],"genre_scores_gemma":[0.9704888,0.00108608,0.0006433299,0.0007756012,0.00003203208,0.00001799706,0.0001172579,0.00003847165,0.02680041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04745203,"threshold_uncertainty_score":0.2798945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1361790172902609,"score_gpt":0.2981980964091511,"score_spread":0.1620190791188901,"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."}}