{"id":"W3209306483","doi":"10.5281/zenodo.4554623","title":"Thread Lift – Face Lift procedures in Toronto","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lift (data mining); Thread (computing); Computer science; Operating system; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003325548,0.0003191105,0.0001157401,0.0004487911,0.007251187,0.001966481,0.0005885474,0.001122799,0.1067888],"category_scores_gemma":[0.0007764106,0.0003729307,0.0003013857,0.0009333859,0.002556151,0.0008111773,0.002632369,0.001733559,0.009214963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01627468,"about_ca_system_score_gemma":0.01661016,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6240761,"about_ca_topic_score_gemma":0.8845071,"domain_scores_codex":[0.999473,0.000045862,0.00001529638,0.00006454855,0.0002420985,0.0001592505],"domain_scores_gemma":[0.9995888,0.00004388752,0.00003192349,0.00003011137,0.00006183451,0.0002434224],"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":[0.0002367055,0.0001462877,0.008040848,0.0004536165,0.00002131926,0.01147871,0.03993214,0.0005413212,0.006213468,0.05696598,0.7181358,0.1578338],"study_design_scores_gemma":[0.000008095428,0.00004887796,0.01709381,0.0002076963,0.000004580242,0.003202738,0.0147284,0.0001056702,0.0006490007,0.001043881,0.9628723,0.00003493903],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1379857,0.007303029,0.00176246,0.02732151,0.004585385,0.0001927318,0.003533616,0.0005116535,0.8168038],"genre_scores_gemma":[0.3846161,0.005152921,0.00202862,0.003485568,0.0004832241,0.0000613992,0.001411253,0.000506599,0.6022543],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3759239,"threshold_uncertainty_score":0.7562757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05291282479050205,"score_gpt":0.278471395461085,"score_spread":0.225558570670583,"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."}}