{"id":"W4391711395","doi":"","title":"« Francophone perspectives on the articulation between learning at work and learning through work »","year":2018,"lang":"en","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":"Université de Sherbrooke","funders":"","keywords":"Articulation (sociology); Work (physics); French; Computer science; Artificial intelligence; Linguistics; Natural language processing; Engineering; Political science; Philosophy; Mechanical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00749279,0.0008109679,0.0002197739,0.001064229,0.009724778,0.01803838,0.001690955,0.007358793,0.01126586],"category_scores_gemma":[0.005261476,0.0003469799,0.0003922459,0.001489707,0.02277704,0.008318409,0.006509895,0.003370122,0.001846073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01398059,"about_ca_system_score_gemma":0.007169445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1335683,"about_ca_topic_score_gemma":0.1083933,"domain_scores_codex":[0.991547,0.005086512,0.0001645712,0.0005469566,0.0008774713,0.001777364],"domain_scores_gemma":[0.9931262,0.004215328,0.0004502664,0.0005070812,0.0004503787,0.001250861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001040204,0.00008010221,0.001723876,0.0001814292,0.000008682901,0.001791013,0.4147169,0.0002988596,0.0008835895,0.5029381,0.03583681,0.04143658],"study_design_scores_gemma":[0.0000139,0.00003673432,0.00343153,0.0005260833,0.000007480282,0.001083795,0.1349985,0.000297704,0.0003937228,0.02278885,0.8363873,0.00003438614],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1137174,0.02094856,0.01351947,0.144593,0.001303675,0.00006769736,0.0002006411,0.000141018,0.7055086],"genre_scores_gemma":[0.8889808,0.005090795,0.001542625,0.007931718,0.0002968932,0.00006159292,0.00005250426,0.00009251662,0.09595056],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1335683,"threshold_uncertainty_score":0.2655817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07125287689484072,"score_gpt":0.3386572661119877,"score_spread":0.267404389217147,"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."}}