{"id":"W1527806246","doi":"10.1109/icnn.1994.374713","title":"Using adaptive logic networks for quick recognition of particles","year":2002,"lang":"en","type":"article","venue":"","topic":"Radiation Detection and Scintillator Technologies","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"CERN","keywords":"Unary operation; Computer science; Artificial neural network; Monotonic function; Artificial intelligence; Property (philosophy); Theoretical computer science; Mathematics; Discrete 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":[0.0004709622,0.0005080335,0.0002605511,0.0004932473,0.0003627973,0.0009349585,0.0009544889,0.0006178466,0.003959714],"category_scores_gemma":[0.00205212,0.0002657059,0.0002541852,0.0004499356,0.000492501,0.001698352,0.0004174724,0.0005805038,0.0007276887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005520757,"about_ca_system_score_gemma":0.0003335805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002651344,"about_ca_topic_score_gemma":0.003308689,"domain_scores_codex":[0.9997426,0.00005780891,0.00001381826,0.00007287326,0.0000843626,0.00002852814],"domain_scores_gemma":[0.999245,0.0004563856,0.00007046057,0.00006819511,0.0001379249,0.00002194987],"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":[0.0004488157,0.0001106209,0.001927002,0.0001556314,0.00006650932,0.0002251029,0.0001331004,0.2181474,0.08077522,0.02963526,0.002658279,0.6657171],"study_design_scores_gemma":[0.00001912041,0.00006577904,0.0003468467,0.000009206728,0.00001852203,0.00008466277,0.00001538385,0.9609309,0.02348583,0.01155094,0.00345491,0.00001791693],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04374842,0.0003468755,0.949105,0.0002432154,0.00006353699,0.00003968331,0.00005428298,0.001703765,0.004695082],"genre_scores_gemma":[0.5652553,0.0004511141,0.4276798,0.0002630804,0.0000630936,0.00008915631,0.0002369529,0.0001254849,0.005835981],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003959714,"threshold_uncertainty_score":0.0132466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1142742397678254,"score_gpt":0.2772893676230381,"score_spread":0.1630151278552127,"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."}}