{"id":"W3094954024","doi":"10.1002/ccd.29336","title":"<scp>CHIP</scp> fellowships: Carving a path for complex <scp>PCI</scp>","year":2020,"lang":"en","type":"letter","venue":"Catheterization and Cardiovascular Interventions","topic":"Coronary Interventions and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto General Hospital; University of Toronto; University Health Network","funders":"","keywords":"Medicine; Carving; Chip; Path (computing); Key (lock); Revascularization; Conventional PCI; Internal medicine; Computer network; Myocardial infarction; Computer science; Telecommunications; Operating system","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004014749,0.0006948407,0.001429826,0.000426022,0.0004295823,0.0003017925,0.000334839,0.0006440174,0.00009571321],"category_scores_gemma":[0.00188637,0.0007182296,0.007101535,0.0003967631,0.0002067657,0.0001599692,0.0002610639,0.001019108,0.00008453757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001274041,"about_ca_system_score_gemma":0.0001202302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002777276,"about_ca_topic_score_gemma":0.000005295785,"domain_scores_codex":[0.9962127,0.0003172168,0.001091226,0.001091724,0.000642552,0.000644599],"domain_scores_gemma":[0.9971068,0.0005865462,0.0003587824,0.001103163,0.0005258883,0.0003188564],"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":[0.000005070919,0.0002813678,0.0004741577,0.005089578,0.004679085,0.0004061282,0.0007027152,0.00003417697,0.0002295266,0.0001526119,0.9836739,0.004271632],"study_design_scores_gemma":[0.00209672,0.0007619039,0.001262538,0.002300616,0.005231864,0.0004228539,0.0008924288,0.001153914,0.00007533141,0.0003588288,0.98527,0.0001730334],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.02148947,0.03944703,0.8300099,0.07361221,0.004920404,0.01041961,0.006939188,0.001479458,0.01168277],"genre_scores_gemma":[0.2258792,0.01026708,0.01765849,0.510288,0.02485759,0.007476818,0.1128115,0.00221637,0.08854493],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8123513,"threshold_uncertainty_score":0.9995269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06716004263801813,"score_gpt":0.2899139239197991,"score_spread":0.222753881281781,"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."}}