{"id":"W4255735171","doi":"10.1086/690748","title":"News, Programs, Publications, and Awards","year":2017,"lang":"en","type":"article","venue":"The Papers of the Bibliographical Society of America","topic":"Library Science and Administration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Library science; Political science; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0005310979,0.00006749779,0.0001208885,0.0001077189,0.001737962,0.0002274796,0.001211453,0.00006221486,0.00003596262],"category_scores_gemma":[0.0001414055,0.0000370134,0.0002771041,0.002920531,0.006434059,0.0004580537,0.0001656433,0.0001137878,7.096443e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003417218,"about_ca_system_score_gemma":0.0001201228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003614802,"about_ca_topic_score_gemma":0.000125595,"domain_scores_codex":[0.9989418,0.0001004631,0.0001611563,0.0001413638,0.0004674248,0.0001877835],"domain_scores_gemma":[0.9988917,0.0001047219,0.0003424242,0.0005095099,0.00006774005,0.00008394228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001938336,0.00025589,0.7585025,0.00003758716,0.0001399055,6.030977e-8,0.009614587,0.000001557178,0.002051312,0.03485664,0.07433214,0.1201885],"study_design_scores_gemma":[0.000141235,0.00009219776,0.6060111,0.00002896872,0.00003598066,4.270027e-7,0.01080262,0.00004126668,0.0001310336,0.005656389,0.3769492,0.0001096048],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3231843,0.0006265158,0.00004403339,0.6076474,0.0002202874,0.0006922863,0.00001718257,0.0000734784,0.06749449],"genre_scores_gemma":[0.9915637,0.005905442,0.001059298,0.0009333035,0.00006582175,0.000008659999,0.000001248636,0.000003550422,0.0004589705],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6683794,"threshold_uncertainty_score":0.9995617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03251131402280723,"score_gpt":0.3096267359506071,"score_spread":0.2771154219277999,"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."}}