{"id":"W2357051493","doi":"","title":"Method of Anterior Chamber Diameter Forecasting System Based on B Pneural Network","year":2007,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Sensor and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial neural network; Simulation; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002253712,0.0001508934,0.0002472854,0.00006072206,0.00006268812,0.00001521898,0.000111559,0.00005915873,0.000002996706],"category_scores_gemma":[2.934629e-7,0.0001463797,0.00009822351,0.0002210893,0.00001311189,0.00003458189,0.00001665626,0.0001014292,0.00001697065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000551282,"about_ca_system_score_gemma":0.000003871376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000506937,"about_ca_topic_score_gemma":0.000004455463,"domain_scores_codex":[0.9990366,0.00002156515,0.0003815284,0.0001883093,0.00009118829,0.0002808303],"domain_scores_gemma":[0.9993697,0.000196617,0.0000734329,0.0002538992,0.00004559856,0.00006069207],"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":[0.00002553847,0.00004181589,0.0005880679,0.0003709788,0.00006308212,0.000008190418,0.0001510444,0.5683147,0.06690121,0.0007470273,0.0003613696,0.362427],"study_design_scores_gemma":[0.0004717108,0.00003196405,0.001188723,0.0001603947,0.00002171611,0.00005229312,0.00003208658,0.9516577,0.008774299,0.00002627452,0.03733613,0.0002467833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004511103,0.00009631138,0.9922609,0.000008870014,0.00005844708,0.000537256,0.00001216513,0.0002619273,0.002253054],"genre_scores_gemma":[0.6596887,5.03768e-7,0.3397727,0.00005756113,0.0003450213,0.0000805021,0.000006557284,0.0000304739,0.00001800709],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6551776,"threshold_uncertainty_score":0.5969189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01012460001399005,"score_gpt":0.2337752044967051,"score_spread":0.223650604482715,"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."}}