{"id":"W1912268362","doi":"10.3917/gen.097.0109","title":"L'analyse des correspondances multiples au service de l'enquête de terrain","year":2014,"lang":"fr","type":"article","venue":"Genèses","topic":"Education, sociology, and vocational training","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Humanities; Political science; Sociology; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003618551,0.0001866208,0.0002269946,0.00007753727,0.001158175,0.00008855536,0.000409125,0.0002250607,0.0002910737],"category_scores_gemma":[0.002771375,0.0002009409,0.0001175959,0.0005001811,0.001836295,0.0002798483,0.00003588044,0.0001785422,0.0001613152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000390441,"about_ca_system_score_gemma":0.001312311,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01891969,"about_ca_topic_score_gemma":0.02616305,"domain_scores_codex":[0.9966604,0.001847313,0.0002477468,0.0003093048,0.0002056053,0.0007296748],"domain_scores_gemma":[0.9963902,0.00278352,0.0001748439,0.0001892133,0.0002189504,0.0002432335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001525517,0.000184271,0.3647082,0.0001806729,0.0001505581,0.00000126804,0.5218039,0.0005951954,0.001239553,0.03391326,0.003726593,0.07348126],"study_design_scores_gemma":[0.000309228,0.00007109228,0.282238,0.0001957995,0.0001586253,0.000009936813,0.3260949,0.002484276,0.0003887779,0.02116966,0.3664565,0.0004232474],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9526013,0.003548665,0.003730794,0.02805992,0.002220629,0.0001289567,0.00002194952,0.00007317379,0.009614639],"genre_scores_gemma":[0.9607347,0.0008705271,0.02283099,0.002681816,0.005445171,0.00004812076,0.0000194765,0.0000202462,0.00734898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3627299,"threshold_uncertainty_score":0.991607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2198610243669114,"score_gpt":0.4419618452641347,"score_spread":0.2221008208972233,"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."}}