{"id":"W215674542","doi":"10.4000/praxematique.1184","title":"La transcription perceptuelle au service du corpus de conversations naturelles","year":2010,"lang":"fr","type":"article","venue":"Cahiers de praxématique","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Humanities; 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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001776872,0.0002960124,0.0002748561,0.000143205,0.0004150722,0.0003586322,0.0007672021,0.001306314,0.0001621461],"category_scores_gemma":[0.0004750186,0.0003327571,0.0001616562,0.000533133,0.000476885,0.0007413313,0.00004100707,0.001742785,0.0003822726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004988645,"about_ca_system_score_gemma":0.001628415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003475335,"about_ca_topic_score_gemma":0.005616697,"domain_scores_codex":[0.9973286,0.0009034771,0.0003671274,0.0004487748,0.0002671444,0.0006848413],"domain_scores_gemma":[0.997937,0.0005226886,0.0001716494,0.0005942084,0.000293821,0.0004805923],"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":[0.00004416701,0.000267782,0.003550678,0.0005898456,0.0001031048,0.0001748546,0.1960565,0.0002729847,0.1940858,0.5803132,0.01216344,0.01237758],"study_design_scores_gemma":[0.003056094,0.0002733895,0.03707076,0.0004786001,0.000231472,0.003570662,0.008360479,0.1421761,0.04008053,0.02912915,0.7339138,0.001658935],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5651388,0.001372293,0.3668587,0.02930787,0.007821838,0.0006451908,0.00006008682,0.0002966556,0.02849861],"genre_scores_gemma":[0.9715169,0.0002008718,0.02116869,0.003272742,0.0007618229,0.00006315741,0.00002829099,0.00003638697,0.002951127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7217504,"threshold_uncertainty_score":0.9999902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01203365795115668,"score_gpt":0.2333522431902527,"score_spread":0.221318585239096,"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."}}