{"id":"W2424225960","doi":"10.7748/ns.23.35.20.s22","title":"A net gain for Kenya","year":2009,"lang":"en","type":"article","venue":"Nursing Standard","topic":"Science, Research, and Medicine","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Canadian Navy","funders":"","keywords":"Pound (networking); Raising (metalworking); Work (physics); Political science; Engineering; Computer science; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00115187,0.0008642849,0.0004027721,0.0006212262,0.005314604,0.003626665,0.0006478522,0.003868477,0.1646811],"category_scores_gemma":[0.003194084,0.0003135623,0.0004750843,0.0004364816,0.0009312934,0.002535488,0.003908052,0.003618921,0.04139959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002037904,"about_ca_system_score_gemma":0.0119814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02746076,"about_ca_topic_score_gemma":0.07350589,"domain_scores_codex":[0.9993169,0.0001249148,0.00002283086,0.00006198103,0.0002184737,0.0002548885],"domain_scores_gemma":[0.9971961,0.0001050825,0.00006034977,0.00009716817,0.0005333135,0.002007951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001196252,0.00003995737,0.0003514504,0.00009023213,0.000006759914,0.0001344493,0.0000516692,0.00002496425,0.0003189703,0.004509553,0.9696592,0.02469322],"study_design_scores_gemma":[0.00003101622,0.00004237624,0.001823276,0.00009973752,0.000006672216,0.000144188,0.0003022438,0.00002345171,0.00009647504,0.0006442864,0.9967763,0.000009936587],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01013891,0.01840203,0.0008258001,0.4709072,0.09332316,0.0002535414,0.003878678,0.0007683933,0.4015023],"genre_scores_gemma":[0.03363627,0.009454252,0.002742262,0.07397806,0.004344966,0.0001638683,0.001809414,0.0001564054,0.8737145],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1646811,"threshold_uncertainty_score":0.5509131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03504548839510732,"score_gpt":0.4005793515620584,"score_spread":0.3655338631669511,"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."}}