{"id":"W2413918082","doi":"10.7748/ns.21.50.61.s53","title":"Student life - dealing with differences","year":2007,"lang":"en","type":"article","venue":"Nursing Standard","topic":"Global Health Workforce Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"St Mary's Hospital","funders":"","keywords":"Student life; Psychology; Medical education; Gerontology; Computer science; Medicine; Library 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":[0.001058444,0.0001845449,0.0003423447,0.00008818093,0.001147305,0.00001801598,0.0001825562,0.0001564852,0.000425379],"category_scores_gemma":[0.00008549177,0.0001381156,0.00003133196,0.0002225811,0.0001381076,0.00007556613,0.00002428576,0.0005270755,0.00007534711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005995103,"about_ca_system_score_gemma":0.0003017698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001281663,"about_ca_topic_score_gemma":0.0003896484,"domain_scores_codex":[0.9974187,0.0001289105,0.000515712,0.0002903552,0.0006934384,0.0009528872],"domain_scores_gemma":[0.9984786,0.0003913322,0.0002051588,0.0002727137,0.000239921,0.0004122837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001839475,0.0001130775,0.8828169,0.0001746682,0.0000461301,0.00004335699,0.02560491,0.00001850167,0.00002999153,0.03889334,0.00844894,0.04197072],"study_design_scores_gemma":[0.004204339,0.00175957,0.7395365,0.01279745,0.0001241125,0.000009527721,0.114817,0.00003356803,0.0001420406,0.003784736,0.1219844,0.0008068146],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8849465,0.0007479188,0.008001774,0.001946427,0.001182311,0.0006578586,0.00001644199,0.0002848554,0.102216],"genre_scores_gemma":[0.9939706,0.00004007197,0.003753412,0.0009342438,0.0004085178,0.00001219052,0.000004680886,0.00003179352,0.0008444752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1432804,"threshold_uncertainty_score":0.8824259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05110021091961907,"score_gpt":0.4780021474495685,"score_spread":0.4269019365299495,"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."}}