{"id":"W2140812479","doi":"10.1142/s0219878904000057","title":"SENSORY INFORMATION ACQUISITION FOR MONITORING AND CONTROL OF INTELLIGENT MECHATRONIC SYSTEMS","year":2004,"lang":"en","type":"article","venue":"International Journal of Information Acquisition","topic":"Sensor Technology and Measurement Systems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Garfield Weston Foundation","keywords":"Mechatronics; Computer science; Workcell; Automation; Data acquisition; Control engineering; Artificial intelligence; Systems engineering; Robot; Engineering","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":[0.000865843,0.0001113628,0.0001904223,0.000688334,0.00006778414,0.0001773828,0.0004024217,0.000114399,0.000003974597],"category_scores_gemma":[0.0001342378,0.0001040563,0.00009507006,0.0001128132,0.000030831,0.005591029,0.00001967745,0.0001098543,0.000009911553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002840226,"about_ca_system_score_gemma":0.00009830335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001201773,"about_ca_topic_score_gemma":1.417284e-7,"domain_scores_codex":[0.9981296,0.00003629289,0.001036359,0.00006151728,0.0006091344,0.0001270755],"domain_scores_gemma":[0.9965689,0.00006462578,0.001343644,0.0001279592,0.001831734,0.00006320514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001379901,0.0002106164,0.003225392,0.0006290414,0.00119343,0.00001113483,0.009549128,0.1058897,0.09905247,0.6944477,0.0003953618,0.08401617],"study_design_scores_gemma":[0.02611104,0.002742632,0.01221099,0.003164742,0.0002324582,0.003014938,0.009185371,0.06307229,0.8341101,0.03230949,0.01272708,0.001118859],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0683714,0.0002113757,0.9279127,0.0007468294,0.002293515,0.0003040998,0.00002153464,0.00004114926,0.0000974651],"genre_scores_gemma":[0.9943903,0.00009149007,0.005121307,0.0001887235,0.0001741782,0.00001440019,0.00001415989,0.000003004895,0.00000240421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.926019,"threshold_uncertainty_score":0.4243293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01348859410230376,"score_gpt":0.2520813077962559,"score_spread":0.2385927136939522,"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."}}