{"id":"W3138751991","doi":"10.7202/1075704ar","title":"Un aperçu de la recherche à Bibliothèque et Archives Canada","year":2021,"lang":"fr","type":"article","venue":"Archives","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Library and Archives Canada","funders":"National Science Board; York University; Social Sciences and Humanities Research Council of Canada; National Research Council Canada; University at Albany; University of Toronto; Strong; Centre National de la Recherche Scientifique; University of Windsor; National Science Foundation; University of Washington; McGill University; Arizona State University; Research Institute, Georgia Institute of Technology; Yale University; National Aeronautics and Space Administration; University of California, Los Angeles; University of Minnesota; University of British Columbia; U.S. Department of Defense","keywords":"Humanities; Political science; Art","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.02213087,0.0006455554,0.001152882,0.01775985,0.01557416,0.02126345,0.001938638,0.003270069,0.02771581],"category_scores_gemma":[0.08055909,0.0007024094,0.0009671329,0.04935125,0.009314398,0.006465888,0.005936495,0.004197197,0.003413724],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09125503,"about_ca_system_score_gemma":0.2528792,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8674849,"about_ca_topic_score_gemma":0.8962309,"domain_scores_codex":[0.9425012,0.01060492,0.002599314,0.003565321,0.03652854,0.004200645],"domain_scores_gemma":[0.8522999,0.04262413,0.008018382,0.00757036,0.07855202,0.01093526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003267382,0.00008971498,0.03572733,0.00413543,0.0002337807,0.001026746,0.02949512,0.0006760263,0.002759618,0.1937212,0.3667787,0.3650297],"study_design_scores_gemma":[0.00001576708,0.00002417721,0.02779772,0.00150726,0.0000589454,0.0002328818,0.0113251,0.0002078219,0.001037818,0.004601304,0.9531247,0.00006649105],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.08474767,0.1417977,0.007156976,0.3972678,0.009689979,0.0004628486,0.01305848,0.0009474494,0.3448711],"genre_scores_gemma":[0.5730649,0.1559624,0.01375057,0.04518317,0.005213,0.0004936235,0.006620666,0.001084963,0.1986267],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9822401,"threshold_uncertainty_score":0.6621047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6317529281274052,"score_gpt":0.5616780748897119,"score_spread":0.07007485323769336,"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."}}