{"id":"W1984765652","doi":"10.1063/1.4771811","title":"Representing potential energy surfaces with neural networks and high dimensional model representations","year":2012,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Icon; Citation; Computer science; Information retrieval; Download; Filter (signal processing); World Wide Web; Computer vision","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":[0.0006630167,0.0002361008,0.0002477187,0.00007271,0.0004416233,0.0005132775,0.0003317533,0.00008281582,0.0002707168],"category_scores_gemma":[0.0001350576,0.0001882018,0.00002460663,0.0001929441,0.0003540795,0.001412696,0.0003620773,0.0001626782,0.00001030077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000194223,"about_ca_system_score_gemma":0.0000423519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005056478,"about_ca_topic_score_gemma":0.00000844291,"domain_scores_codex":[0.9979311,0.00004090842,0.0003003454,0.0005751602,0.0004911229,0.0006613791],"domain_scores_gemma":[0.9990006,0.00005967949,0.0002561049,0.0001739968,0.0002819343,0.0002276918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009556863,0.00006309635,0.1000491,0.0000297335,0.000009273113,0.000003499383,0.0008201528,0.1028252,0.7793606,0.01613686,0.0003023499,0.0003046037],"study_design_scores_gemma":[0.0002191596,0.00004829399,0.01797416,0.0000293889,0.00002493632,0.00007776985,0.0001358065,0.9726213,0.007734966,0.0008567229,0.00001263344,0.0002648436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9339743,0.00006541868,0.06420512,0.0005180187,0.000292061,0.0001111953,0.000004619783,0.0001615139,0.0006677777],"genre_scores_gemma":[0.9858355,0.000008082699,0.01331834,0.0001742239,0.0002041882,0.00003200236,0.000007425333,0.00002375096,0.000396478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8697961,"threshold_uncertainty_score":0.7674646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01572722990635225,"score_gpt":0.2484498426432185,"score_spread":0.2327226127368662,"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."}}