{"id":"W22184809","doi":"10.7202/1043650ar","title":"Remédiation et interaction dans le milieu textuel","year":2014,"lang":"fr","type":"article","venue":"Sens public","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Humanities; Art; 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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003572316,0.0001915198,0.0001620041,0.0001066331,0.0002065667,0.002860701,0.0002846335,0.0001229951,0.00004477365],"category_scores_gemma":[0.0004006285,0.0001629457,0.00009698242,0.0004333536,0.00009851754,0.007590582,0.0001794994,0.000214761,0.0006207101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001165667,"about_ca_system_score_gemma":0.0001473974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002031642,"about_ca_topic_score_gemma":0.00147498,"domain_scores_codex":[0.9984542,0.0002230435,0.0002651571,0.0003866971,0.0002577546,0.0004131508],"domain_scores_gemma":[0.9987777,0.0001193462,0.0001479307,0.0004514463,0.0002411488,0.0002623522],"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":[0.000003048863,0.0001860256,0.00007415898,0.00002015227,0.00001870937,0.00001002097,0.00260522,0.0001392046,0.003006573,0.7953212,0.03468791,0.1639277],"study_design_scores_gemma":[0.0003002514,0.0001328634,0.00963699,0.00004915386,0.000007543404,0.0002110618,0.0002346346,0.05861192,0.001590709,0.01174323,0.9171927,0.0002889556],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1035727,0.0009450508,0.1017603,0.1277333,0.005561958,0.0002361027,0.00001380635,0.0003017027,0.6598752],"genre_scores_gemma":[0.9358629,0.00004131869,0.001215936,0.002715457,0.0004872438,0.000002370601,0.000037295,0.00001392585,0.05962357],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8825048,"threshold_uncertainty_score":0.9981744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1909773004973152,"score_gpt":0.3085798793117175,"score_spread":0.1176025788144023,"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."}}