{"id":"W7112110579","doi":"","title":"Adding Libraries to the Equation: Mathematical Sciences’ Underutilization of Academic Librarians","year":2025,"lang":"","type":"preprint","venue":"CU Scholar (University of Colorado Boulder)","topic":"Library Science and Information Literacy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Information literacy; Discipline; Academic library; Literacy; Library instruction","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01530692,0.0001712074,0.0004392494,0.007356899,0.003065181,0.01021679,0.001543123,0.001296745,0.008569716],"category_scores_gemma":[0.09624298,0.0004785839,0.0005902712,0.009889296,0.00386134,0.01059017,0.006601322,0.001589189,0.001494851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004302439,"about_ca_system_score_gemma":0.009732864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02239375,"about_ca_topic_score_gemma":0.03165824,"domain_scores_codex":[0.9809431,0.01010512,0.00245525,0.001007916,0.003816992,0.001671605],"domain_scores_gemma":[0.8881281,0.05437397,0.03055028,0.006044499,0.01341558,0.007487447],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002558222,0.000168244,0.5215144,0.0009833265,0.0001231498,0.0009912429,0.1337736,0.0001121527,0.0005165745,0.008193227,0.03630658,0.2970616],"study_design_scores_gemma":[0.00004266033,0.0001945732,0.5836151,0.00154432,0.0002039623,0.003389878,0.3013566,0.0006171687,0.001467484,0.005084783,0.1023438,0.0001396483],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9060631,0.006219603,0.001148643,0.05523793,0.0002011604,0.00005075384,0.0005081561,0.0001451353,0.03042557],"genre_scores_gemma":[0.9865068,0.003389782,0.0006699505,0.006567128,0.0002159015,0.00002860409,0.0001872796,0.00007118726,0.002363325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9897832,"threshold_uncertainty_score":0.08095169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0692379255127815,"score_gpt":0.3044124074323644,"score_spread":0.2351744819195829,"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."}}