{"id":"W3174046134","doi":"10.3390/app11135806","title":"Automatic Wheels and Camera Calibration for Monocular and Differential Mobile Robots","year":2021,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"JetBrains Research","keywords":"Computer vision; Artificial intelligence; Computer science; Robot calibration; Camera auto-calibration; Robot; Calibration; Camera resectioning; Mobile robot; Position (finance); Process (computing); Robot kinematics; Mathematics","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":[0.000571517,0.0006954591,0.0005401145,0.0009487501,0.0004885021,0.0005284948,0.001083493,0.0006022453,0.002385105],"category_scores_gemma":[0.002128829,0.0005244411,0.0003551422,0.000753149,0.000527872,0.000759113,0.001017571,0.0005250613,0.00114464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005153224,"about_ca_system_score_gemma":0.000804156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002839038,"about_ca_topic_score_gemma":0.004347376,"domain_scores_codex":[0.9988443,0.0001971455,0.00003694254,0.0002869931,0.000546072,0.00008855498],"domain_scores_gemma":[0.999115,0.0001331032,0.0001843803,0.0002754391,0.0002584478,0.00003356556],"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":[0.0003257137,0.00009727204,0.003405701,0.0003845966,0.00004980147,0.0001729201,0.0003300344,0.01702234,0.1672331,0.004655306,0.002796789,0.8035265],"study_design_scores_gemma":[0.000148918,0.001115544,0.03945577,0.000200909,0.0001324307,0.002802303,0.0003976348,0.4720423,0.4111483,0.006387687,0.06588123,0.000287126],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02071,0.00042992,0.9754934,0.00004575399,0.00006520931,0.00007662562,0.00004928396,0.001155171,0.001974692],"genre_scores_gemma":[0.5291655,0.0004285055,0.4643992,0.0001030833,0.00003475054,0.0001327475,0.0002052586,0.0001629176,0.005368042],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002839038,"threshold_uncertainty_score":0.007978976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01076350637045274,"score_gpt":0.2171666313407186,"score_spread":0.2064031249702658,"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."}}