{"id":"W2106891397","doi":"10.1002/ccd.21532","title":"Robot or not robot!","year":2008,"lang":"en","type":"letter","venue":"Catheterization and Cardiovascular Interventions","topic":"Renal and Vascular Pathologies","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal Heart Institute","funders":"","keywords":"Library science; Citation; Medicine; Art history; Artificial intelligence; History; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001571933,0.0008454364,0.0008722795,0.0004006911,0.00394071,0.003050505,0.0009688392,0.05322996,0.01401768],"category_scores_gemma":[0.01339067,0.000490007,0.0008978239,0.0002480245,0.002732506,0.00329113,0.002063857,0.03856791,0.01093904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002114427,"about_ca_system_score_gemma":0.001906802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002528,"about_ca_topic_score_gemma":0.007431843,"domain_scores_codex":[0.9985722,0.0004063214,0.0001092611,0.000230489,0.0003967583,0.0002849342],"domain_scores_gemma":[0.9976512,0.001060733,0.0001725324,0.00009145081,0.0003353849,0.0006886877],"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":[0.00003998756,0.00002683255,0.000715239,0.00003552648,0.00001289637,0.003003897,0.0001602452,0.00011041,0.0001572273,0.003684601,0.9783206,0.01373251],"study_design_scores_gemma":[0.00004756983,0.00008137032,0.0009370174,0.0001798293,0.00001831191,0.004676447,0.0005032723,0.0004520287,0.0001451096,0.01044908,0.9824595,0.00005035408],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00046008,0.001215525,0.000375699,0.9664196,0.01797177,0.00001046647,0.00002136888,0.000061475,0.013464],"genre_scores_gemma":[0.005554992,0.0009151156,0.0003454478,0.94846,0.01509645,0.00003324794,0.00002044751,0.00002174862,0.02955258],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.05322996,"threshold_uncertainty_score":0.04689378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1311660612485255,"score_gpt":0.3112518398208817,"score_spread":0.1800857785723563,"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."}}