{"id":"W1988908320","doi":"10.1007/s10763-007-9089-4","title":"The Literacy Component of Mathematical and Scientific Literacy","year":2007,"lang":"en","type":"article","venue":"International Journal of Science and Mathematics Education","topic":"Science Education and Pedagogy","field":"Social Sciences","cited_by":176,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; University of Victoria","funders":"Division of Mathematical Sciences; National Science Council; European Science Education Research Association","keywords":"Scientific literacy; Argument (complex analysis); Literacy; Component (thermodynamics); Mathematics education; Curriculum; Information literacy; Science education; Citizenship; Cognition; Science, technology, society and environment education; Democracy; Metacognition; Engineering ethics; Psychology; Pedagogy; Sociology; Political science; Chemistry; Engineering; Politics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001070822,0.000233974,0.000335267,0.002270542,0.0005966216,0.002558667,0.0003359453,0.0007509163,0.00711578],"category_scores_gemma":[0.02516672,0.0003130671,0.0004174226,0.001576297,0.001992287,0.00317607,0.001831025,0.001457291,0.0004528793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008355002,"about_ca_system_score_gemma":0.002276371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003388628,"about_ca_topic_score_gemma":0.004228197,"domain_scores_codex":[0.9987755,0.0002636914,0.0001039103,0.000138517,0.0005212885,0.0001970882],"domain_scores_gemma":[0.980202,0.01171246,0.002810627,0.001139667,0.002762333,0.001372981],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002804454,0.00105408,0.634851,0.0004492514,0.0001927294,0.0007780378,0.01095838,0.001139129,0.002918374,0.1595547,0.002820759,0.1850031],"study_design_scores_gemma":[0.00002972899,0.0001980179,0.8999711,0.0002397909,0.0001384666,0.0008643021,0.004958945,0.002702421,0.001567286,0.08276282,0.006523892,0.00004330405],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9043183,0.0005444803,0.002890975,0.002636105,0.00005391871,0.0000705569,0.0002022076,0.00002831055,0.08925513],"genre_scores_gemma":[0.997675,0.0001651836,0.0008533435,0.00009503433,0.00002601255,0.00002319645,0.00006303686,0.000003827095,0.001095369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00711578,"threshold_uncertainty_score":0.02380466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0371477592733911,"score_gpt":0.4466430167350829,"score_spread":0.4094952574616918,"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."}}