{"id":"W4232314446","doi":"10.32920/ryerson.14636379.v1","title":"E-Reserve Redefined: One Canadian library experience","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Library Science and Administration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Outreach; World Wide Web; Library science; Space (punctuation); Interactivity; Subject (documents); Library classification; Commons; Scope (computer science); Collection development; Dimension (graph theory); Computer science; Business; Sociology; Public relations; Political science; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[],"category_scores_codex":[0.0002279408,0.0001501395,0.000187463,0.0001286502,0.0006010427,0.00168274,0.0009768358,0.0003308062,0.01505608],"category_scores_gemma":[0.0001462955,0.0001578767,0.0001000663,0.000451457,0.0002994419,0.002179506,0.000364478,0.000321613,0.00007808569],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007666865,"about_ca_system_score_gemma":0.00950547,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6796522,"about_ca_topic_score_gemma":0.7813468,"domain_scores_codex":[0.9980312,0.0001664361,0.0002419061,0.0005445787,0.00052078,0.0004951272],"domain_scores_gemma":[0.9987068,0.00004732285,0.00008282303,0.0004438524,0.00004613071,0.0006730505],"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":[0.0000160397,0.0002628418,0.127648,0.0001239537,0.00007105327,0.0004668578,0.1832983,0.00008379646,0.000268244,0.5389735,0.1391117,0.009675681],"study_design_scores_gemma":[0.0001922356,0.00007203465,0.02054318,0.0004006123,0.00002382089,0.00000255976,0.1130122,0.0002876547,0.004466804,0.02837797,0.8309955,0.001625416],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2506799,0.0002002305,0.00002109717,0.03596725,0.001055234,0.0002624087,0.0000255841,0.000175801,0.7116125],"genre_scores_gemma":[0.944544,0.0002949428,0.002981482,0.002728277,0.0005588397,0.00003594726,0.0002040258,0.00001228826,0.04864024],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6938641,"threshold_uncertainty_score":0.9993536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07041067935379745,"score_gpt":0.3112440364498106,"score_spread":0.2408333570960132,"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."}}