{"id":"W2998030295","doi":"10.1299/jsmermd.2019.2a1-n09","title":"The Open Source 3D Vision Platform for Robots","year":2019,"lang":"en","type":"article","venue":"The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Grieg Seafood (Canada)","funders":"","keywords":"Commercialization; Robot; Computer science; Key (lock); Software; Feature (linguistics); Open source; Artificial intelligence; Open platform; Human–computer interaction; Computer vision; Operating system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006369352,0.0002871776,0.0003597473,0.00007514105,0.0003318504,0.0004537503,0.0007882258,0.0001523713,0.00001040635],"category_scores_gemma":[0.00005126943,0.0001855147,0.00008186827,0.0001710649,0.00009282308,0.000322083,0.0002322953,0.0002724053,0.00001251069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005257112,"about_ca_system_score_gemma":0.00005420852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001312509,"about_ca_topic_score_gemma":0.000008585853,"domain_scores_codex":[0.9985072,0.000006012187,0.0004100642,0.0003022909,0.0002967516,0.0004776541],"domain_scores_gemma":[0.9988048,0.0001769224,0.0001713444,0.000236445,0.0005059676,0.0001044922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001039881,0.00003050883,0.00002689891,0.0001212057,0.00005869609,6.396477e-8,0.0006321946,0.4233101,0.002220464,0.5671571,0.0009371009,0.005401677],"study_design_scores_gemma":[0.001014731,0.0008183643,0.00003749323,0.0001834391,0.00006252884,0.000003831482,0.002643856,0.9672188,0.00198879,0.01966104,0.006004866,0.000362322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.434128,0.002523664,0.4792767,0.01566041,0.003681975,0.01487476,0.0002602295,0.0009667853,0.04862748],"genre_scores_gemma":[0.9929686,0.001011998,0.004291235,0.0001254858,0.0000701806,0.00003872388,0.00001752836,0.00007585884,0.001400437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5588406,"threshold_uncertainty_score":0.7565068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01694927877174067,"score_gpt":0.2450307004930022,"score_spread":0.2280814217212615,"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."}}