{"id":"W2789731256","doi":"10.18162/fp.2018.a139","title":"Articuler langue et écriture : un travail de planification... signifiant!","year":2018,"lang":"fr","type":"article","venue":"Formation et profession","topic":"Linguistics and Discourse Analysis","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Art; Humanities; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.009369472,0.002155537,0.0009876861,0.002642969,0.003188143,0.01623621,0.001860266,0.003954004,0.007707129],"category_scores_gemma":[0.02243153,0.0009034171,0.001462663,0.002906263,0.01519297,0.02515588,0.005665619,0.006238657,0.002719313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003900504,"about_ca_system_score_gemma":0.006678825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02380339,"about_ca_topic_score_gemma":0.01014509,"domain_scores_codex":[0.9929128,0.004644889,0.0002477654,0.0009118011,0.0009544218,0.0003283815],"domain_scores_gemma":[0.9913042,0.005696145,0.0003768773,0.001311774,0.001117694,0.0001934264],"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":[0.00009119373,0.00002931433,0.0006001312,0.000447303,0.00003287473,0.0001644908,0.01320292,0.002310066,0.001757376,0.8424036,0.007052073,0.1319086],"study_design_scores_gemma":[0.00002955165,0.00005096197,0.0008895124,0.0007439249,0.00003266092,0.0003266289,0.01233862,0.01961073,0.004135447,0.6916744,0.2700832,0.00008429496],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01708687,0.01321711,0.8832181,0.02406602,0.00144302,0.000166836,0.0003885071,0.00200535,0.05840805],"genre_scores_gemma":[0.3502026,0.01733101,0.5914556,0.002422497,0.001199509,0.0005043112,0.001671636,0.002631919,0.03258083],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02380339,"threshold_uncertainty_score":0.04955113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03001571889708682,"score_gpt":0.3069001678881814,"score_spread":0.2768844489910946,"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."}}