{"id":"W4206855173","doi":"10.58079/amwh","title":"Affordance : Co-concevoir des environnements numériques pour les rendre affordants","year":2020,"lang":"fr","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Education, sociology, and vocational training","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":[0.005219014,0.001339552,0.001011861,0.003148765,0.001381188,0.005957662,0.001717229,0.001515485,0.04059681],"category_scores_gemma":[0.02680953,0.0006341387,0.001299844,0.002978447,0.001240211,0.009889958,0.008310483,0.001751013,0.01303675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001287126,"about_ca_system_score_gemma":0.003193219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02149944,"about_ca_topic_score_gemma":0.02357405,"domain_scores_codex":[0.9963224,0.001176013,0.0002984021,0.0007669964,0.001214559,0.000221665],"domain_scores_gemma":[0.9925905,0.002936126,0.0008491962,0.001187591,0.001678524,0.0007579262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009939804,0.0002770659,0.0241845,0.001434787,0.0001965151,0.0001779203,0.00563861,0.004877172,0.003555067,0.04683472,0.1314591,0.7803707],"study_design_scores_gemma":[0.0002345919,0.0004223147,0.03886807,0.001436919,0.0002270451,0.0003513104,0.007333416,0.02982957,0.006353073,0.08967856,0.8248329,0.0004322587],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1067139,0.02107101,0.5224509,0.03590752,0.003690229,0.000961357,0.03939462,0.04411861,0.225692],"genre_scores_gemma":[0.4591658,0.005825139,0.4457,0.001371886,0.0007011641,0.001473297,0.0215601,0.008078439,0.05612401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04059681,"threshold_uncertainty_score":0.1358099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1116802271935631,"score_gpt":0.3551638511387545,"score_spread":0.2434836239451915,"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."}}