{"id":"W4407585816","doi":"10.3390/bs15020211","title":"Estimating the Minimum Sample Size for Neural Network Model Fitting—A Monte Carlo Simulation Study","year":2025,"lang":"en","type":"article","venue":"Behavioral Sciences","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Monte Carlo method; Sample size determination; Artificial neural network; Computer science; Sample (material); Statistics; Mathematics; Artificial intelligence; Physics","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0006082848,0.0001258425,0.0001290665,0.00002649371,0.001462514,0.0004635955,0.001206822,0.00002851392,0.000001269504],"category_scores_gemma":[0.00008372139,0.0000842557,0.00007002144,0.0009011614,0.0001179923,0.0003675751,0.0002703886,0.00009066801,7.380787e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000192388,"about_ca_system_score_gemma":0.00006430018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002057614,"about_ca_topic_score_gemma":0.0001055505,"domain_scores_codex":[0.9986118,0.00004872695,0.0002686016,0.0004558403,0.0002516914,0.0003633545],"domain_scores_gemma":[0.9983283,0.001079242,0.0001146915,0.000357842,0.00007630809,0.00004367307],"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":[0.00000170014,0.00007026423,0.006901583,0.000001173794,0.00000129648,1.753483e-7,0.0002130391,0.9717218,0.0000142705,0.001043073,0.0003952208,0.01963645],"study_design_scores_gemma":[0.0001307488,0.000111414,0.005215193,0.000008753769,0.00001768832,2.621772e-7,0.00009564126,0.9884979,0.000004236228,0.005745221,0.00007384211,0.00009917343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7296454,0.00003287438,0.2675818,0.001456451,0.0003427538,0.0008074802,0.000003934683,0.00009686477,0.00003242262],"genre_scores_gemma":[0.8960677,2.486224e-7,0.1032266,0.0002780937,0.0001054669,0.0001881067,3.08333e-7,0.000003388885,0.0001301216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1664222,"threshold_uncertainty_score":0.9998375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08374965081522025,"score_gpt":0.3862219202035477,"score_spread":0.3024722693883274,"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."}}