{"id":"W120798794","doi":"","title":"Information needs of residents during inpatient and outpatient rotations: identifying effective personal digital assistant applications.","year":2003,"lang":"en","type":"article","venue":"PubMed","topic":"Healthcare Systems and Technology","field":"Business, Management and Accounting","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Advancing Health Outcomes","funders":"","keywords":"Medicine; BitTorrent tracker; Medical education; Family medicine; Computer 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":[0.0002457551,0.00009233528,0.0001346391,0.000455575,0.0001444991,0.0001724911,0.00006029848,0.0000633987,0.000003247108],"category_scores_gemma":[0.0002523527,0.00008939433,0.00002668527,0.0004474059,0.00003871195,0.001497163,0.00005542582,0.0000808823,0.00001349077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006900211,"about_ca_system_score_gemma":0.000009931519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002637445,"about_ca_topic_score_gemma":0.00002021342,"domain_scores_codex":[0.9991666,0.00001094219,0.0003574462,0.00007386375,0.0001912438,0.0001998672],"domain_scores_gemma":[0.9993731,0.00002635154,0.0003039374,0.000104555,0.0001754068,0.00001660035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0000441874,0.000117441,0.4527835,0.00197584,0.00006561658,8.16351e-7,0.001829891,0.00000690524,0.00002948246,0.04380322,0.00008827176,0.4992548],"study_design_scores_gemma":[0.0005272196,0.000007794028,0.9865658,0.00003872545,0.00001452463,0.000002897654,0.003339194,0.00003019003,0.00009774671,0.001001219,0.008253091,0.0001215895],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992989,0.0001079607,0.001163531,0.0001006551,0.0001286104,0.001746599,0.000007272221,0.00006475612,0.003691636],"genre_scores_gemma":[0.9972688,0.000004536849,0.00001733509,0.00005698843,0.00004621791,0.002548522,0.00001905626,0.000007659653,0.00003088724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5337822,"threshold_uncertainty_score":0.3645395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01161071941311066,"score_gpt":0.2069698636621042,"score_spread":0.1953591442489936,"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."}}