{"id":"W1997471720","doi":"10.4271/2013-01-2118","title":"Robotic Tooling Self-Calibration","year":2013,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Calibration; Computer science; Artificial intelligence; 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":[0.000811141,0.000851222,0.000608701,0.0008293675,0.0004714722,0.000792362,0.001540633,0.0008694482,0.003857287],"category_scores_gemma":[0.001940132,0.0005296435,0.0007116327,0.0006079299,0.0007108173,0.001289371,0.00198946,0.0008938714,0.001599507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004985076,"about_ca_system_score_gemma":0.0007932247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009981727,"about_ca_topic_score_gemma":0.0008899007,"domain_scores_codex":[0.9982505,0.0002047679,0.00007113277,0.0004544324,0.0009419422,0.00007715116],"domain_scores_gemma":[0.9985898,0.0001925228,0.0001730596,0.0006239805,0.0003971398,0.00002345831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001083617,0.00009502329,0.001976288,0.0005586987,0.00006164895,0.0002730353,0.0004246996,0.1552436,0.1529518,0.02632559,0.004763179,0.6572181],"study_design_scores_gemma":[0.00003130566,0.0003326331,0.002714849,0.00009267781,0.00004921138,0.001260649,0.0001193103,0.7665616,0.1694039,0.008065818,0.0512545,0.000113563],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007159051,0.0001418029,0.9864108,0.00002780376,0.00004626406,0.00005035705,0.00002463805,0.001537904,0.004601398],"genre_scores_gemma":[0.4573119,0.0004486431,0.5275126,0.0001148054,0.000045695,0.0001730792,0.0002966136,0.0005029088,0.01359368],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003857287,"threshold_uncertainty_score":0.01290393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008235088766015752,"score_gpt":0.2043755121513852,"score_spread":0.1961404233853695,"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."}}