{"id":"W7128748619","doi":"","title":"Diagnostic 2020 sur l’expertise québécoise en mobilisation des connaissances","year":2021,"lang":"fr","type":"other","venue":"Bibliothèque et Archives nationales du Québec (Québec government)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Perspective (graphical); Work (physics); Subject (documents); Government (linguistics)","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003151872,0.0005781733,0.00022992,0.002478497,0.007541896,0.006085671,0.0009968642,0.002677941,0.04996486],"category_scores_gemma":[0.006262117,0.0002184682,0.0002788013,0.002334166,0.002141406,0.002400851,0.003136967,0.00215315,0.004668587],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05913523,"about_ca_system_score_gemma":0.1613666,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9767909,"about_ca_topic_score_gemma":0.9881158,"domain_scores_codex":[0.9975541,0.0002534263,0.00004119732,0.0001334686,0.001105631,0.0009122934],"domain_scores_gemma":[0.9921598,0.0004564417,0.0001828247,0.0001721784,0.004627064,0.002401732],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00008369825,0.00005367063,0.01103078,0.0002073977,0.0000146815,0.0003249746,0.006784523,0.000332613,0.001023316,0.07688877,0.7954687,0.1077868],"study_design_scores_gemma":[0.000006186327,0.00001020543,0.01786,0.0001929126,0.00000682052,0.00004149624,0.004751589,0.0001516554,0.0003517672,0.001513547,0.9750954,0.00001854169],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02546042,0.006609258,0.001780596,0.1019406,0.001606315,0.0002129677,0.00697041,0.0003542862,0.8550652],"genre_scores_gemma":[0.2341922,0.00389014,0.003225997,0.01053348,0.0002084997,0.0001982173,0.004174279,0.0001513496,0.7434258],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9968481,"threshold_uncertainty_score":0.4290581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01289930090399648,"score_gpt":0.2312008261443912,"score_spread":0.2183015252403947,"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."}}