{"id":"W4391925251","doi":"10.3390/technologies12020027","title":"ARSIP: Automated Robotic System for Industrial Painting","year":2024,"lang":"en","type":"article","venue":"Technologies","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Mitacs","keywords":"Painting; Computer science; Engineering; Human–computer interaction; Visual arts; Art","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003903299,0.0007444663,0.0004348909,0.0006016375,0.0003638073,0.0005351398,0.00146213,0.000546601,0.0191182],"category_scores_gemma":[0.0004896699,0.0003103707,0.0004608817,0.0002696986,0.0003115156,0.000538866,0.001103916,0.0005504138,0.006757879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000281912,"about_ca_system_score_gemma":0.000901613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001000607,"about_ca_topic_score_gemma":0.001082746,"domain_scores_codex":[0.9996343,0.0000284993,0.00001861247,0.00008713642,0.0001923889,0.0000392019],"domain_scores_gemma":[0.9998036,0.0000271871,0.00002427225,0.00005672994,0.00006337458,0.00002483067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006756441,0.0002926413,0.00332759,0.001206154,0.0001250661,0.0008272285,0.000392644,0.05837343,0.2533361,0.009082496,0.05946023,0.6129008],"study_design_scores_gemma":[0.0003851476,0.001280776,0.009468145,0.000148703,0.0001210873,0.001638411,0.0001286665,0.5180626,0.1405788,0.005525547,0.3224377,0.0002245304],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03820021,0.0004597901,0.8276417,0.0001849066,0.0003084206,0.0006563967,0.001573589,0.1068386,0.02413647],"genre_scores_gemma":[0.4505086,0.0004502122,0.508221,0.0002808675,0.0001035946,0.001308326,0.003428634,0.002357149,0.03334156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0191182,"threshold_uncertainty_score":0.06395674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05112157319539057,"score_gpt":0.242265850985059,"score_spread":0.1911442777896685,"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."}}