{"id":"W2517858966","doi":"10.21914/anziamj.v57i0.10435","title":"Preparing non-traditional students for engineering degrees","year":2016,"lang":"en","type":"article","venue":"ANZIAM Journal","topic":"Mathematics Education and Programs","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bachelor; Government (linguistics); Economic shortage; Engineering education; Mathematics; Mathematics education; Engineering; Political science; Engineering management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005659772,0.0001007545,0.0001325903,0.00006884676,0.0001155962,0.0001078855,0.000222951,0.00004190037,0.0002859654],"category_scores_gemma":[0.0003808517,0.00006686868,0.0001056861,0.00004451167,0.00001316621,0.0001417462,0.00002224409,0.00008404283,0.00002319933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005013181,"about_ca_system_score_gemma":0.00004427173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.259744e-7,"about_ca_topic_score_gemma":9.98162e-7,"domain_scores_codex":[0.9991243,0.00001127937,0.0002866633,0.00009434304,0.0002735023,0.000209847],"domain_scores_gemma":[0.9990539,0.0004617912,0.0001359231,0.0001246212,0.0001010685,0.0001227093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001348426,0.002861582,0.0180041,0.001046687,0.001186531,0.00002041429,0.006919734,0.00004637964,0.007666207,0.317984,0.5341486,0.109981],"study_design_scores_gemma":[0.004788165,0.0004802028,0.005674695,0.001649644,0.0001735576,0.001194193,0.0003784044,0.00211932,0.004210955,0.8153398,0.1630764,0.0009146286],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4169621,0.00006152134,0.5766153,0.0009555118,0.001265554,0.0004980717,0.00001386394,0.0001023638,0.003525768],"genre_scores_gemma":[0.7936226,0.00003584487,0.2014851,0.0000659031,0.001226373,0.00008655142,0.000002330092,0.00004823333,0.003427074],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4973558,"threshold_uncertainty_score":0.3131121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1032359740248044,"score_gpt":0.3665474486031045,"score_spread":0.2633114745783,"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."}}