{"id":"W1615026946","doi":"","title":"Convex combination initialization method for kohonen neural network implemented in the CMOS technology","year":2012,"lang":"en","type":"article","venue":"Infoscience (Ecole Polytechnique Fédérale de Lausanne)","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Initialization; Computer science; Self-organizing map; Artificial neural network; CMOS; Realization (probability); Process (computing); Block (permutation group theory); Artificial intelligence; Computer engineering; Computer architecture; Electronic engineering; Engineering; 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":[0.0002115392,0.0003361598,0.0002848113,0.0002048461,0.0002048246,0.0003659975,0.0006486752,0.0003673387,0.002107473],"category_scores_gemma":[0.0004818212,0.0001759298,0.0003168568,0.0002933407,0.0002437736,0.0004608404,0.0003830871,0.000630762,0.0005371635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003482329,"about_ca_system_score_gemma":0.0004371208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001071553,"about_ca_topic_score_gemma":0.001530629,"domain_scores_codex":[0.9998206,0.00003650798,0.000008819031,0.00002803268,0.00009024118,0.00001579826],"domain_scores_gemma":[0.9998684,0.00004656377,0.00001348227,0.00001754555,0.00004629492,0.000007763811],"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":[0.0001746287,0.00006030473,0.0006155655,0.0002984286,0.00008385093,0.0002382213,0.0001712553,0.4014818,0.09126882,0.05284278,0.004189018,0.4485753],"study_design_scores_gemma":[0.000007805787,0.00003587192,0.0001499672,0.000009127596,0.000008435169,0.00007290634,0.000007582922,0.977176,0.0148159,0.003728384,0.003975704,0.00001236706],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003773294,0.00008688968,0.9937189,0.00003573997,0.00002753474,0.00001722659,0.00001253181,0.0002378868,0.002089967],"genre_scores_gemma":[0.2375191,0.0002796765,0.7576958,0.00009109532,0.00003898654,0.0001180468,0.0000764012,0.0001098446,0.004070971],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002107473,"threshold_uncertainty_score":0.007050216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02214254062588398,"score_gpt":0.3231433696325703,"score_spread":0.3010008290066863,"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."}}