{"id":"W4254033814","doi":"10.32920/ryerson.14661789","title":"Penscriptive Depth-Controlled Robotic Laser Osteotomy","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Intraocular Surgery and Lenses","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Laser; Computer science; Robot; Optical coherence tomography; Imaging phantom; Artificial intelligence; Focus (optics); Robot end effector; Computer vision; Biomedical engineering; Materials science; Optics; Engineering; Physics","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":[0.0001595473,0.0004348062,0.0001715302,0.0002215851,0.0001497926,0.0003463647,0.0006248364,0.0003225503,0.003230277],"category_scores_gemma":[0.0003099077,0.0002238492,0.0001834362,0.0001135957,0.0002954204,0.0003558111,0.0004639169,0.0003626354,0.0005598096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002154745,"about_ca_system_score_gemma":0.0004118501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006375122,"about_ca_topic_score_gemma":0.00114246,"domain_scores_codex":[0.9998127,0.00001432227,0.000007759678,0.00004608583,0.00009725798,0.00002196194],"domain_scores_gemma":[0.9998114,0.00003385004,0.00006233383,0.00003630301,0.00003656005,0.0000195551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003742403,0.0001202283,0.0008735696,0.0001790756,0.00001524474,0.0002209474,0.0001147454,0.01333803,0.8296567,0.002156994,0.001756286,0.151194],"study_design_scores_gemma":[0.00026697,0.002022751,0.01045295,0.00006272626,0.00005223634,0.002787775,0.0000982531,0.3089725,0.6372014,0.00184811,0.03604554,0.0001887933],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2138149,0.0005993593,0.7657663,0.0002139122,0.0001477681,0.0003163221,0.0002457735,0.003144865,0.01575086],"genre_scores_gemma":[0.6762647,0.0002788178,0.3105074,0.000128499,0.00002737912,0.0001799714,0.0001100863,0.00009980075,0.01240321],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003230277,"threshold_uncertainty_score":0.01080632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02650354502762636,"score_gpt":0.2740273269917485,"score_spread":0.2475237819641222,"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."}}