{"id":"W2753995967","doi":"10.29173/iasl7458","title":"Awards with Rewards","year":2021,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Library Science and Administration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Censorship; Collection development; Quality (philosophy); Curriculum; Selection (genetic algorithm); Public relations; Psychology; Sociology; Library science; Political science; Law; Computer science; Epistemology; Artificial intelligence; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003391418,0.0001090915,0.000127353,0.00004110485,0.0004762172,0.0005887853,0.0002811404,0.00008611873,0.0006112584],"category_scores_gemma":[0.0002162096,0.00009188254,0.00003343042,0.0006078964,0.0003494446,0.002362693,0.00004678838,0.0001351555,0.00006854015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002815285,"about_ca_system_score_gemma":0.00165329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001818517,"about_ca_topic_score_gemma":0.0002494599,"domain_scores_codex":[0.9985573,0.00001946765,0.0001395689,0.0003379611,0.0005859988,0.0003597207],"domain_scores_gemma":[0.9986954,0.00002111007,0.00007108445,0.00006970966,0.0009371786,0.0002054802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005622298,0.0001450448,0.07986547,0.0000428817,0.00002443514,0.00006932009,0.6459376,5.923345e-7,0.0008199425,0.2402878,0.01959721,0.01315341],"study_design_scores_gemma":[0.0003424872,0.0003007631,0.01412991,0.0001094709,0.00001959381,0.00002777934,0.5947644,0.00003882918,0.007484167,0.01119022,0.3711056,0.0004868285],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.813637,0.00003050559,0.0001353568,0.01218851,0.0001613032,0.0001100459,0.00001047317,0.0001527267,0.1735741],"genre_scores_gemma":[0.9828436,0.00004458925,0.0009602067,0.0007016134,0.0002905698,0.00001148479,0.000006144546,0.000006525915,0.0151352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3515084,"threshold_uncertainty_score":0.6692851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03047865827384736,"score_gpt":0.2960509520966224,"score_spread":0.265572293822775,"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."}}