{"id":"W2976291963","doi":"10.1075/jicb.18033.he","title":"Co-developing science literacy and foreign language literacy through “Concept + Language Mapping”","year":2019,"lang":"en","type":"article","venue":"Journal of Immersion and Content-Based Language Education","topic":"Second Language Learning and Teaching","field":"Arts and Humanities","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Literacy; Mathematics education; Scientific literacy; Intervention (counseling); Computer science; Thematic analysis; Pedagogy; Thematic map; Psychology; Sociology; Qualitative research; Science education; Geography; Cartography","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00066374,0.0001928734,0.0002825006,0.0003794297,0.0003779639,0.0005562968,0.0001941797,0.0000477969,0.001230033],"category_scores_gemma":[0.0001462087,0.0001508963,0.00008991922,0.0001091163,0.0002018137,0.001190033,0.00002719873,0.0004026298,0.00002292727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008218035,"about_ca_system_score_gemma":0.0002768867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008189359,"about_ca_topic_score_gemma":0.000009669123,"domain_scores_codex":[0.9986662,0.0001232453,0.0004094063,0.0002501473,0.000281869,0.0002691879],"domain_scores_gemma":[0.9988472,0.0001539629,0.0004541784,0.0001925211,0.0002298642,0.0001222137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005050978,0.00008139452,0.001930132,0.0001040066,0.00002917226,0.00002098853,0.3713024,0.00000112758,0.02078119,0.00467832,0.0003056284,0.6007151],"study_design_scores_gemma":[0.001126634,0.0001668296,0.0004608262,0.0006024707,0.00003129743,0.00008505738,0.9872602,0.0001548331,0.006019488,0.000005249619,0.003837643,0.0002494331],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841678,0.008768297,0.0002775576,0.0006326867,0.0006915317,0.0001655233,0.000008020652,0.00002604332,0.005262584],"genre_scores_gemma":[0.9913462,0.00002917491,0.001275533,0.002798643,0.0005221014,0.000002952357,0.00004163884,0.00002089571,0.003962851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6159578,"threshold_uncertainty_score":0.999683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02100227909050686,"score_gpt":0.2946432755973483,"score_spread":0.2736409965068414,"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."}}