{"id":"W4412456718","doi":"10.54393/fbt.v5i2.176","title":"STEM Education Unites a Divided World","year":2025,"lang":"en","type":"article","venue":"Futuristic Biotechnology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Political science","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":[],"consensus_categories":[],"category_scores_codex":[0.0002042819,0.000171173,0.0001777316,0.0004356484,0.0001194006,0.00003372169,0.0004939809,0.0004997118,0.00003881231],"category_scores_gemma":[0.0002594215,0.0001523168,0.00006877929,0.0005461372,0.0004074782,0.000002380117,0.0003545041,0.0002614893,0.00007449459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003494974,"about_ca_system_score_gemma":0.0004341043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002450166,"about_ca_topic_score_gemma":0.0001082051,"domain_scores_codex":[0.9987742,0.00004340043,0.0003167704,0.0003308447,0.0001508187,0.0003839519],"domain_scores_gemma":[0.9990751,0.00003390217,0.00007222115,0.0005940491,0.0001323673,0.00009236034],"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":[0.0001072334,0.0003389412,0.001992738,0.0002680854,0.000163929,0.000003606887,0.00003745208,0.000002449656,0.1368908,0.0248387,0.1618861,0.67347],"study_design_scores_gemma":[0.0003735138,0.0002063271,0.001533518,0.00004947272,0.00002624904,0.000007571745,0.0003094531,0.0001491397,0.1683886,0.002486021,0.8262632,0.0002069495],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.726146,0.01725967,0.09820233,0.0587419,0.008607306,0.00262989,0.0001964951,0.0006610368,0.08755541],"genre_scores_gemma":[0.9705948,0.0009883415,0.002784944,0.001544166,0.0003194677,0.0000627865,0.0001948475,0.0000163354,0.02349434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6732631,"threshold_uncertainty_score":0.6211299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01039220150754043,"score_gpt":0.277635799583196,"score_spread":0.2672435980756556,"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."}}