{"id":"W2910668666","doi":"10.7202/1052708ar","title":"Information: People still count","year":2018,"lang":"en","type":"article","venue":"Documentation et bibliothèques","topic":"Library Collection Development and Digital Resources","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Library Association","funders":"","keywords":"Theme (computing); Joint (building); Public relations; Association (psychology); Library science; Political science; Sociology; Engineering ethics; World Wide Web; Engineering; Computer science; Psychology; Architectural engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0001557071,0.00009572357,0.00007722065,0.001286914,0.0001261649,0.008128263,0.0003449999,0.00002911206,0.001537785],"category_scores_gemma":[0.00003782837,0.00008618966,0.00002789863,0.003554015,0.00003194667,0.05360067,0.0001293369,0.00004027099,0.000676061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003488536,"about_ca_system_score_gemma":0.0001330327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003313886,"about_ca_topic_score_gemma":0.00002534239,"domain_scores_codex":[0.9991253,0.00003226679,0.0002227134,0.0001190651,0.0003508249,0.0001498089],"domain_scores_gemma":[0.9994217,0.00006407432,0.00009704969,0.000178069,0.0001681979,0.00007096714],"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":[0.00004033988,0.00007358834,0.02551656,0.00003038522,0.00004747128,0.000001582248,0.02765895,0.00002223614,0.00009045342,0.5573238,0.3664263,0.0227684],"study_design_scores_gemma":[0.0004560994,0.0001604723,0.04002398,0.00001253786,0.000002131255,0.000008807336,0.0002714404,0.001364582,0.004817963,0.01325325,0.9393918,0.0002369534],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07081149,0.00012704,0.5288284,0.004614033,0.0009664043,0.0003421101,0.000006239956,0.001010155,0.3932942],"genre_scores_gemma":[0.9727865,0.0002332588,0.01338901,0.007145266,0.0001135642,0.000034715,0.00003260428,0.00000625503,0.006258847],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.901975,"threshold_uncertainty_score":0.9993749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01294931623024773,"score_gpt":0.2676999751727574,"score_spread":0.2547506589425096,"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."}}