{"id":"W2210732300","doi":"","title":"Improving accuracy in robotized fibre placement using force and visual servoing external hybrid control scheme","year":2014,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Robotiq (Canada)","funders":"","keywords":"Visual servoing; Position (finance); Task (project management); Robot; Process (computing); Scheme (mathematics); Engineering; Computer science; Artificial intelligence; Simulation; Computer vision; 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":[0.0001991884,0.0002403725,0.0002189557,0.0001532032,0.0002177694,0.0002367666,0.0005793474,0.0004098352,0.001350273],"category_scores_gemma":[0.0005709975,0.0001363553,0.0001319151,0.0001595648,0.000214246,0.0003243854,0.0004443804,0.0002530758,0.0002362401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002421197,"about_ca_system_score_gemma":0.0002305729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001966048,"about_ca_topic_score_gemma":0.001870273,"domain_scores_codex":[0.9998178,0.00002190681,0.000006931213,0.00003894607,0.0000954819,0.00001896248],"domain_scores_gemma":[0.9996151,0.0001100943,0.00004673997,0.00007896391,0.0001330946,0.00001606806],"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":[0.0005984061,0.0001071955,0.001167746,0.0002005404,0.00002807985,0.0001664039,0.0001966269,0.1648439,0.592146,0.005027946,0.001036358,0.2344808],"study_design_scores_gemma":[0.00002537152,0.000241953,0.00139653,0.00001022918,0.00001014912,0.0001259742,0.00001834522,0.8604301,0.1351857,0.0007176105,0.00182078,0.00001730303],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1952567,0.0003637548,0.799951,0.00007984029,0.00008815518,0.00003242575,0.00003368508,0.0006237755,0.003570714],"genre_scores_gemma":[0.8948184,0.00008194119,0.101987,0.0000140422,0.00001201192,0.0000173998,0.00003470584,0.0000261179,0.003008373],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001966048,"threshold_uncertainty_score":0.004517138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008976944855936227,"score_gpt":0.2216351749665369,"score_spread":0.2126582301106006,"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."}}