{"id":"W2979739707","doi":"10.29173/iasl7230","title":"Making and Implementing an Environmental Studies Database for Teacher Librarians: Metadata Education for Teacher Librarians","year":2016,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metadata; Database catalog; Christian ministry; World Wide Web; Computer science; Meta Data Services; Subject (documents); Metadata repository; Information retrieval; Political 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":[0.03935809,0.0003319973,0.0007994891,0.009454501,0.006961184,0.01343029,0.003503255,0.001597936,0.008677249],"category_scores_gemma":[0.05684342,0.001216112,0.0006269941,0.008350541,0.001726782,0.02336973,0.007548691,0.001782321,0.004528655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004329183,"about_ca_system_score_gemma":0.02093867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01157496,"about_ca_topic_score_gemma":0.02106985,"domain_scores_codex":[0.9813722,0.009165484,0.003945212,0.00182428,0.00294333,0.0007494523],"domain_scores_gemma":[0.9238268,0.02302082,0.005520794,0.01804261,0.02346714,0.006121928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003333979,0.002064561,0.113569,0.001537294,0.00007858394,0.0006070531,0.04910977,0.001347287,0.01313732,0.02315197,0.05314026,0.7419235],"study_design_scores_gemma":[0.0003534239,0.0006023616,0.05186966,0.001554116,0.0002907982,0.0006157163,0.07223696,0.006667756,0.0244143,0.01155458,0.8294683,0.0003720508],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.497718,0.003184491,0.2743947,0.04648635,0.0009014755,0.01063969,0.009968913,0.01948963,0.1372167],"genre_scores_gemma":[0.3592008,0.001755086,0.6076738,0.002549364,0.0003005107,0.003057304,0.007675245,0.001171031,0.01661684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03935809,"threshold_uncertainty_score":0.208148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1175689772214568,"score_gpt":0.3766110337024509,"score_spread":0.2590420564809941,"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."}}