{"id":"W2223988311","doi":"","title":"Preservice Teachers as Mentors: Learning Science, Technology, Engineering, and Mathematics (STEM) Topics Through School Outreach Activities","year":2010,"lang":"en","type":"article","venue":"Society for Information Technology & Teacher Education International Conference","topic":"Education and Technology Integration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Outreach; Mathematics education; Science education; Pedagogy; Psychology; 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":[0.0008180339,0.0002111307,0.000177277,0.0008660809,0.0009440488,0.0004125605,0.0009171275,0.0006772474,0.0002742691],"category_scores_gemma":[0.00147523,0.0002270621,0.00009520778,0.001111535,0.001334809,0.002574165,0.0001396532,0.001040836,0.00004478029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000365612,"about_ca_system_score_gemma":0.001548767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002009253,"about_ca_topic_score_gemma":0.00009002542,"domain_scores_codex":[0.9984531,0.00001242325,0.0004402539,0.0002918393,0.0004345611,0.000367869],"domain_scores_gemma":[0.9979886,0.00006169264,0.0003930049,0.0003143832,0.001139795,0.0001024679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002952272,0.0001247916,0.00791212,0.00002292693,0.00005099488,1.9617e-8,0.02622883,0.00000298104,0.001971425,0.94513,0.001322151,0.0172308],"study_design_scores_gemma":[0.0002884108,0.0000593814,0.0002394377,0.00004846063,0.00003222883,0.00001033669,0.3230047,0.001033687,0.004536583,0.04098293,0.6294807,0.0002831688],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8407233,0.00008594125,0.004695992,0.06851885,0.002496331,0.00123335,0.00001361423,0.001475654,0.08075697],"genre_scores_gemma":[0.9493654,0.0001648057,0.03505241,0.0003630817,0.0002443354,0.0007629167,0.00007016741,0.0000171572,0.01395976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9041471,"threshold_uncertainty_score":0.9259323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01497109526295092,"score_gpt":0.3286205760663862,"score_spread":0.3136494808034352,"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."}}