{"id":"W4408345225","doi":"10.22329/jtl.v19i1.8810","title":"Emerging Digital Technologies: Building Competencies of STEM Pre-Service Teachers","year":2025,"lang":"en","type":"article","venue":"Journal of Teaching and Learning","topic":"Digital literacy in education","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Service (business); Business; Knowledge management; Computer science; Engineering management; Engineering; Marketing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001098921,0.00009566024,0.0002054971,0.0003501858,0.0002025132,0.0003796525,0.0005525392,0.00004264365,3.172017e-7],"category_scores_gemma":[0.0006557929,0.0000822416,0.00005760351,0.0002850198,0.00003124021,0.001553852,0.0002172103,0.0009166519,3.589444e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004824084,"about_ca_system_score_gemma":0.00006809708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001130702,"about_ca_topic_score_gemma":3.359578e-7,"domain_scores_codex":[0.9990045,0.0001093561,0.0004143697,0.0001307501,0.0001979908,0.0001429846],"domain_scores_gemma":[0.9988266,0.0004132415,0.0004613879,0.000150713,0.000119124,0.00002897205],"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":[0.000007212071,0.00005579707,0.03438764,0.00007974342,0.00005538899,0.000003205439,0.01729192,0.002454759,0.002342479,0.009254621,0.00007823692,0.933989],"study_design_scores_gemma":[0.003343671,0.001915651,0.05395164,0.01323527,0.0002390367,0.0008244318,0.2710702,0.1641945,0.01054171,0.03353194,0.4452747,0.001877201],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8796823,0.0007003195,0.1155447,0.001561266,0.0002522785,0.0000311479,2.403579e-7,0.00008560653,0.002142152],"genre_scores_gemma":[0.9638516,0.000008505402,0.03574955,0.00003794612,0.00002306656,5.489957e-7,2.066784e-7,0.000004539952,0.0003240839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9321118,"threshold_uncertainty_score":0.3982447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008350565580655367,"score_gpt":0.271577754154554,"score_spread":0.2632271885738987,"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."}}