{"id":"W2095083114","doi":"10.7202/012241ar","title":"Présentation : TALN, Web et corpus","year":2003,"lang":"fr","type":"article","venue":"Revue québécoise de linguistique","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Natural language processing; Linguistics; World Wide Web; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002874707,0.001134199,0.001410624,0.005513968,0.002670349,0.007594299,0.001743623,0.001734974,0.3685432],"category_scores_gemma":[0.01505093,0.0005351561,0.0005760731,0.005659664,0.0008942824,0.00528565,0.002909794,0.002995897,0.1434004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002707955,"about_ca_system_score_gemma":0.004121065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02018468,"about_ca_topic_score_gemma":0.01952007,"domain_scores_codex":[0.9984871,0.0002986619,0.0001019839,0.0002223045,0.0007978946,0.00009209017],"domain_scores_gemma":[0.9939396,0.001629972,0.0001626614,0.0006791705,0.00291584,0.0006727541],"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":[0.00007557537,0.00001368247,0.00005526545,0.00008086208,0.00000460778,0.00003863695,0.00002597321,0.00007662281,0.0003019891,0.003177825,0.985453,0.01069609],"study_design_scores_gemma":[0.00003510584,0.00001027044,0.0002978932,0.00005652727,0.000007678962,0.00007947582,0.00007730121,0.001114388,0.0007463589,0.004064572,0.9934935,0.00001694862],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.005566483,0.006500751,0.04962596,0.1172377,0.1793469,0.0008798699,0.3248273,0.02667397,0.289341],"genre_scores_gemma":[0.02134693,0.003449192,0.01491457,0.007016032,0.02511925,0.000780959,0.1969164,0.009553934,0.7209029],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.3685432,"threshold_uncertainty_score":0.9006965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.017651259057589,"score_gpt":0.3071661175675773,"score_spread":0.2895148585099883,"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."}}