{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002891032,0.0003797909,0.0005079248,0.001013622,0.002803725,0.002703181,0.001394166,0.0007591723,0.03642905],"category_scores_gemma":[0.008060119,0.0003468505,0.0006278837,0.001120205,0.0006663082,0.0012217,0.004579958,0.001375406,0.0148025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482981,"about_ca_system_score_gemma":0.007933396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005718343,"about_ca_topic_score_gemma":0.02113213,"domain_scores_codex":[0.9973103,0.0004163269,0.0001418169,0.0003151716,0.001190903,0.0006255233],"domain_scores_gemma":[0.982605,0.001152448,0.001896512,0.0006938446,0.001827788,0.01182439],"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":[0.0006755304,0.01622079,0.2573963,0.001377512,0.00004587044,0.000903147,0.01805091,0.0005750982,0.0088566,0.001854049,0.03117424,0.66287],"study_design_scores_gemma":[0.0001698822,0.01014279,0.8231986,0.0006374597,0.00006678911,0.0006772915,0.02574219,0.0005821888,0.004038176,0.002222182,0.132423,0.00009933495],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9532357,0.001263547,0.0009039787,0.002743202,0.0002167454,0.0008656307,0.0004162561,0.0001516306,0.04020334],"genre_scores_gemma":[0.9283009,0.002366091,0.00751146,0.002904071,0.0001054103,0.0007789184,0.0007481162,0.00004752641,0.05723747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03642905,"threshold_uncertainty_score":0.1218673,"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."}}