{"id":"W2297691789","doi":"10.29173/iasl7690","title":"Determining, Implementing, and Evaluating Training for School Librarians in Rural China","year":2021,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Library Science and Information Literacy","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Promotion (chess); Reading (process); Curriculum; China; Selection (genetic algorithm); Training (meteorology); Library science; Medical education; Psychology; Pedagogy; Political science; Computer science; Medicine; Geography","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":[0.01113033,0.0004670192,0.0005102803,0.002422049,0.002300739,0.001663958,0.00158948,0.0007373165,0.001757857],"category_scores_gemma":[0.0178262,0.0003420878,0.00024899,0.002220158,0.0007293953,0.001341471,0.001444132,0.0004669807,0.0003763416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008172717,"about_ca_system_score_gemma":0.02954509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06345987,"about_ca_topic_score_gemma":0.1298302,"domain_scores_codex":[0.9941266,0.003146729,0.0003325566,0.0003615145,0.001011105,0.001021507],"domain_scores_gemma":[0.9888955,0.002177299,0.001656367,0.0004509283,0.004040526,0.002779261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001022333,0.007500931,0.4386012,0.001519396,0.00007032108,0.0003113332,0.01870912,0.003860892,0.005638465,0.0006942368,0.002700787,0.519371],"study_design_scores_gemma":[0.0007137076,0.01039719,0.9004572,0.0005530203,0.0002836973,0.00008918934,0.05647852,0.005462316,0.01201065,0.0003314478,0.01314385,0.00007919859],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939512,0.0003246622,0.000589106,0.0002641832,0.00001129445,0.001369665,0.00006560812,0.00006392801,0.00336032],"genre_scores_gemma":[0.9884281,0.0005525008,0.007234649,0.0001911833,0.00001134949,0.001126819,0.0002028285,0.00001274381,0.002239854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06345987,"threshold_uncertainty_score":0.126181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06216762712349103,"score_gpt":0.361245950053567,"score_spread":0.2990783229300759,"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."}}