{"id":"W4400483511","doi":"10.2139/ssrn.4890739","title":"Performance Assessment of Experimental Design for Physics-Informed Neural Networks","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Northern British Columbia; University of Waterloo","funders":"","keywords":"Artificial neural network; Management science; Computer science; Engineering; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0006195036,0.0003846719,0.000459792,0.00008069178,0.000178213,0.0001135736,0.0003715693,0.0001314119,0.00005984846],"category_scores_gemma":[0.000001362386,0.0003367031,0.0005236431,0.0001036784,0.00005684253,0.0001172015,0.0002525478,0.003846554,0.000002029074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005842735,"about_ca_system_score_gemma":0.00267523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001309502,"about_ca_topic_score_gemma":0.00000147441,"domain_scores_codex":[0.9971216,0.00006395271,0.0005634763,0.0003454677,0.0002653182,0.001640224],"domain_scores_gemma":[0.9990318,0.00006244694,0.0004537611,0.0002455493,0.0001072151,0.00009916815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001551283,0.0002031069,0.0005025768,0.00008441076,0.0008754554,4.359948e-7,0.000134629,0.8243237,0.0002071201,0.08992058,0.000903163,0.08268975],"study_design_scores_gemma":[0.0005510278,0.0004084464,0.00001632638,0.000117126,0.000128146,0.00001621868,0.0003822377,0.9266563,0.001128964,0.07019453,0.00008747594,0.0003132094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.239354,0.002515805,0.7524192,0.0001578416,0.002802817,0.001022075,0.00002197811,0.00005119778,0.001655062],"genre_scores_gemma":[0.9943898,0.0005284962,0.0009717463,0.00001760411,0.003057621,0.0001462117,0.00006075583,0.00006362032,0.0007641395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7550358,"threshold_uncertainty_score":0.9999085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02598873214362055,"score_gpt":0.3138702569884189,"score_spread":0.2878815248447983,"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."}}