{"id":"W113755896","doi":"","title":"Libraries in Charter Schools: A Content Analysis.","year":2002,"lang":"en","type":"article","venue":"Teacher librarian","topic":"Library Science and Administration","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Charter; Content analysis; Content (measure theory); Charter school; Mathematics education; Political science; Psychology; Sociology; Pedagogy; Mathematics; Social science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005713763,0.0001841954,0.0004075009,0.02249598,0.002829418,0.004228101,0.0007775257,0.000647239,0.005992838],"category_scores_gemma":[0.03695381,0.000286442,0.0003439729,0.0301955,0.001582215,0.004498312,0.00287158,0.0006710034,0.0007950235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009612166,"about_ca_system_score_gemma":0.01409335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05001616,"about_ca_topic_score_gemma":0.05845311,"domain_scores_codex":[0.9918655,0.004017631,0.0009589346,0.0004625445,0.001956753,0.0007386549],"domain_scores_gemma":[0.9548926,0.02899323,0.00516049,0.0008153452,0.008574519,0.001563898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004197393,0.0005458688,0.5237146,0.002893683,0.0001137416,0.0005174578,0.2189408,0.0005474949,0.001085708,0.006829531,0.019039,0.2253524],"study_design_scores_gemma":[0.00003091391,0.0001563041,0.6858004,0.001495754,0.0001923712,0.0002159732,0.2674442,0.0008752697,0.001461884,0.00104472,0.04123166,0.00005050316],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9641135,0.002359639,0.001569422,0.001669223,0.00002892585,0.0009110991,0.007980506,0.0001130241,0.02125457],"genre_scores_gemma":[0.9880604,0.001470815,0.002992296,0.0002507245,0.00003447753,0.0003823676,0.002714796,0.00004558784,0.00404858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05001616,"threshold_uncertainty_score":0.09945005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1344378061704588,"score_gpt":0.2927007906172626,"score_spread":0.1582629844468038,"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."}}