{"id":"W2028537298","doi":"10.1016/s0380-1330(02)70558-3","title":"Great Lakes Educational Needs Assessment: Teachers’ Priorities for Topics, Materials, and Training","year":2002,"lang":"en","type":"article","venue":"Journal of Great Lakes Research","topic":"Water Quality and Resources Studies","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Oceanic and Atmospheric Administration","keywords":"Curriculum; Newspaper; Training (meteorology); Science education; School teachers; Psychology; Environmental education; Sociology; Medical education; Public relations; Pedagogy; Geography; Political science; Medicine; Media studies; Meteorology","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":[0.009221435,0.0003145855,0.0003789154,0.002253088,0.003143655,0.002315924,0.0009913222,0.00160523,0.008533088],"category_scores_gemma":[0.02307254,0.0004189702,0.000427479,0.001127669,0.0004559865,0.001862182,0.002824523,0.001532609,0.0009615101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005019235,"about_ca_system_score_gemma":0.0269386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02375492,"about_ca_topic_score_gemma":0.08137317,"domain_scores_codex":[0.9978176,0.0008762411,0.0001970314,0.00009081818,0.0005186549,0.0004996782],"domain_scores_gemma":[0.9852154,0.00330053,0.0006565575,0.0001980278,0.004969432,0.005660058],"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":[0.0008873594,0.001656248,0.246202,0.001987038,0.00005200719,0.00121552,0.06026242,0.001420773,0.004155499,0.005810307,0.1325641,0.5437868],"study_design_scores_gemma":[0.0003092753,0.001090286,0.5466318,0.002881676,0.0001608532,0.0006950099,0.2493042,0.00547685,0.008611768,0.006012805,0.1785879,0.0002375358],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7700718,0.001747031,0.006161067,0.157384,0.000615817,0.002487398,0.001348301,0.0004206135,0.05976389],"genre_scores_gemma":[0.916275,0.001848469,0.04882015,0.004063654,0.0002308771,0.002470755,0.001279074,0.00008838298,0.02492379],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02375492,"threshold_uncertainty_score":0.04876816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1853418167786525,"score_gpt":0.3650931461889192,"score_spread":0.1797513294102667,"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."}}