{"id":"W2934497975","doi":"","title":"Classifier with Hierarchical Topographical Maps as Internal Representation.","year":2015,"lang":"en","type":"article","venue":"International Conference on Learning Representations","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Artificial intelligence; Classifier (UML); Pattern recognition (psychology); Machine learning; Data mining","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":[0.000480281,0.0004590144,0.000679552,0.0008716306,0.0003864182,0.001297624,0.001254047,0.001190098,0.004726402],"category_scores_gemma":[0.002496291,0.000215598,0.0006764157,0.001065973,0.0002776559,0.001696112,0.0009535113,0.0009039704,0.002605079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00044565,"about_ca_system_score_gemma":0.0007732313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003633959,"about_ca_topic_score_gemma":0.004548136,"domain_scores_codex":[0.999703,0.00005696646,0.00001685432,0.00007428353,0.00008862486,0.0000602724],"domain_scores_gemma":[0.9994165,0.0001768222,0.00004096944,0.0001391829,0.0001906247,0.00003596551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003734777,0.0001897902,0.002458978,0.0002103821,0.0001640381,0.0001933328,0.0001001022,0.08804378,0.01833102,0.02065685,0.04038646,0.8288918],"study_design_scores_gemma":[0.0000278301,0.00008780116,0.000994657,0.00002863873,0.00005326217,0.0001244226,0.00006116341,0.966575,0.006114187,0.02134438,0.004574028,0.00001458803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05843187,0.001401864,0.9186293,0.0008145627,0.0004020194,0.0002094587,0.001907061,0.004029466,0.0141743],"genre_scores_gemma":[0.7405629,0.0006296876,0.239806,0.0004310341,0.0002570059,0.0002440548,0.004366242,0.0002239569,0.01347929],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004726402,"threshold_uncertainty_score":0.01581144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07523832574978477,"score_gpt":0.3500137003630276,"score_spread":0.2747753746132429,"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."}}