{"id":"W2139194126","doi":"10.1109/icar.1997.620246","title":"A novel method to create intelligent sensors with learning capabilities","year":2002,"lang":"en","type":"article","venue":"","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"National Science Foundation","keywords":"Computer science; Knowledge base; Intelligent sensor; Expert system; Artificial intelligence; Wireless sensor network; Base (topology); Real-time computing; Operator (biology); Embedded system; Control engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009770362,0.0006140531,0.0005340521,0.0006245385,0.0005470336,0.001541277,0.00202965,0.001207356,0.003634724],"category_scores_gemma":[0.002060848,0.00052062,0.001002817,0.0004426527,0.002207271,0.002896865,0.001467503,0.001611409,0.001008593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008033032,"about_ca_system_score_gemma":0.001081714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007354232,"about_ca_topic_score_gemma":0.001044672,"domain_scores_codex":[0.9991021,0.0001850828,0.00005474209,0.0002278562,0.0003670095,0.00006328435],"domain_scores_gemma":[0.9992409,0.0003001992,0.00008138371,0.0001974214,0.0001293095,0.00005085354],"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":[0.00004736253,0.0000810675,0.0003592345,0.0003175062,0.00005745012,0.0002009816,0.00040773,0.0501544,0.02194883,0.8195243,0.00304184,0.1038592],"study_design_scores_gemma":[0.00007020227,0.0002211583,0.0001935245,0.0001151585,0.00006695541,0.0006667266,0.0001019745,0.5459815,0.03353765,0.3035518,0.115419,0.00007446429],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008000733,0.00006501623,0.996613,0.0001099799,0.00002986159,0.00004037712,0.00001644261,0.0002931597,0.002032256],"genre_scores_gemma":[0.06714992,0.0001857363,0.9276264,0.0001520334,0.00003288192,0.0003051989,0.000061256,0.00008416301,0.004402324],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003634724,"threshold_uncertainty_score":0.01215935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.033055065345191,"score_gpt":0.2553668760673852,"score_spread":0.2223118107221942,"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."}}