{"id":"W2295604025","doi":"10.13034/jsst.v8i1.51","title":"ENHANCING SCIENTIFIC LITERACY: A RESOURCE FOR TEACHERS","year":2015,"lang":"en","type":"article","venue":"Journal of Student Science and Technology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McMaster University","funders":"","keywords":"Scientific literacy; GRASP; Mathematics education; Curriculum; Science education; Engineering ethics; Psychology; Computer science; Pedagogy; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002983587,0.00007325847,0.0001277508,0.0004371926,0.0001800374,0.0001436046,0.0005903122,0.0001022927,8.564381e-7],"category_scores_gemma":[0.001281854,0.00005375706,0.00003283282,0.0004721435,0.001382935,0.000017495,0.0002999113,0.0001268785,0.000001683532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003535687,"about_ca_system_score_gemma":0.0005561635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.900486e-7,"about_ca_topic_score_gemma":0.000003593403,"domain_scores_codex":[0.9985977,0.00001112583,0.0003013571,0.0001755862,0.0006164621,0.0002978162],"domain_scores_gemma":[0.9983309,0.00001346839,0.000157051,0.000179465,0.001109062,0.0002100757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005883608,0.0001313559,0.007049919,0.0000229482,0.00003264808,0.000005997565,0.001582111,0.000002737134,0.9069984,0.0002374588,0.006400239,0.07747735],"study_design_scores_gemma":[0.002002611,0.003906106,0.002122762,0.00007020363,0.00002797647,0.0002196916,0.009982942,0.0001515485,0.5071662,0.001593198,0.4725189,0.0002378681],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946188,0.0008295393,0.002171295,0.001815426,0.0002460988,0.0001213507,0.000001737029,0.000004533807,0.0001912558],"genre_scores_gemma":[0.9943607,0.00007541918,0.004960356,0.0001158976,0.0001219772,0.000003740894,0.00000139244,0.000004237529,0.0003562647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4661186,"threshold_uncertainty_score":0.509548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02117629395761875,"score_gpt":0.3415338695694924,"score_spread":0.3203575756118737,"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."}}