{"id":"W2889585925","doi":"10.1111/medu.13670","title":"Thinking of selection and widening access as complex and wicked problems","year":2018,"lang":"en","type":"review","venue":"Medical Education","topic":"Medical Education and Admissions","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Wicked problem; Selection (genetic algorithm); Framing (construction); Context (archaeology); Engineering ethics; Frame (networking); Sociology; Management science; Epistemology; Psychology; Computer science; Artificial intelligence; Engineering","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007228253,0.0002219399,0.0009008455,0.0002609359,0.0001323934,0.00004189406,0.00016598,0.0003884186,0.006158409],"category_scores_gemma":[0.01018792,0.0001609647,0.00008547273,0.0004039823,0.0003481417,0.00008964324,0.0001045681,0.000508828,0.00001548036],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006964911,"about_ca_system_score_gemma":0.009248294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001009217,"about_ca_topic_score_gemma":0.0000076387,"domain_scores_codex":[0.9979341,0.0001415826,0.0006615061,0.0003754781,0.0007074946,0.0001798139],"domain_scores_gemma":[0.9980412,0.0002247479,0.000380214,0.00018279,0.0001902605,0.0009808163],"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":[0.000004955291,0.0002619535,0.0000812546,0.01737949,0.00005990823,6.626648e-7,0.0007416763,4.454786e-9,0.000001455162,0.0003343763,0.02966418,0.9514701],"study_design_scores_gemma":[0.000229064,0.000115208,0.0002096319,0.03464994,0.0005012605,0.0004012958,0.0001487002,0.00006467708,0.000001525355,0.0003240189,0.9632198,0.0001349309],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005413693,0.9894337,0.0001105591,0.005928577,0.0006705323,0.0009044235,0.000001451247,0.00005016701,0.002359205],"genre_scores_gemma":[0.0003394964,0.9936755,0.0007971614,0.002990902,0.0007776006,0.00009155636,0.0002204912,0.000031882,0.001075392],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9513351,"threshold_uncertainty_score":0.9981497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1057512818529728,"score_gpt":0.4781506943893093,"score_spread":0.3723994125363365,"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."}}