{"id":"W4400915117","doi":"10.1103/physrevresearch.6.033098","title":"Waddington landscape for prototype learning in generalized Hopfield networks","year":2024,"lang":"en","type":"article","venue":"Physical Review Research","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute; Université de Montréal; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Chan Zuckerberg Initiative; Simons Foundation; Northwestern University; Silicon Valley Community Foundation; National Science Foundation","keywords":"Hopfield network; Computer science; Cognitive science; Artificial intelligence; Artificial neural network; Psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009860308,0.00008588094,0.0001973089,0.00006455726,0.00011297,0.0001878485,0.000513349,0.00002552355,0.00001490821],"category_scores_gemma":[0.0001159809,0.00006380971,0.0001021043,0.001278761,0.00002497095,0.0001515004,0.0001934209,0.0005940216,0.00005921146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002046235,"about_ca_system_score_gemma":0.00005279394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001026502,"about_ca_topic_score_gemma":0.000003865611,"domain_scores_codex":[0.9986051,0.0001698378,0.0001605992,0.0003917675,0.0002708193,0.0004018619],"domain_scores_gemma":[0.998792,0.0007562561,0.00001540715,0.000278875,0.00007946201,0.00007798076],"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":[0.00001161878,0.0001006508,0.00005863057,0.001384596,0.00001192283,0.00001070286,0.00007000236,0.001450966,0.0004877988,0.3699086,0.03902718,0.5874774],"study_design_scores_gemma":[0.0000656579,0.00009881076,0.00002714108,0.0009205186,0.000002508045,0.000001008069,8.907016e-7,0.7735806,0.00006724901,0.01039068,0.214768,0.00007696483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0136985,0.2969813,0.5932935,0.06754569,0.0005109157,0.01503192,0.000005098588,0.001062369,0.01187067],"genre_scores_gemma":[0.9603884,0.02965334,0.002708476,0.0005584102,0.00100206,0.004549099,0.00001610599,0.00003002408,0.001094081],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9466899,"threshold_uncertainty_score":0.2602084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08804667514139429,"score_gpt":0.4502189883582383,"score_spread":0.362172313216844,"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."}}