{"id":"W4412422519","doi":"10.1016/j.aquaculture.2025.742951","title":"The novel model INEDM and two traditional models for estimating the carrying capacity of Hong Kong oyster (Crassostrea hongkongensis) in two aquaculture systems in Guangdong Province of China","year":2025,"lang":"en","type":"article","venue":"Aquaculture","topic":"Marine Bivalve and Aquaculture Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Agriculture","funders":"Basic and Applied Basic Research Foundation of Guangdong Province; Key Technologies Research and Development Program of Guangzhou; Guangdong Science and Technology Department; Guangzhou Municipal Science and Technology Bureau; Department of Agriculture of Guangdong Province; National Natural Science Foundation of China","keywords":"Biology; Aquaculture; Oyster; Fishery; Crassostrea; Carrying capacity; China; Shellfish; Aquatic animal; Ecology; Fish <Actinopterygii>","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001173514,0.0007827134,0.0005497608,0.0006748906,0.0004594848,0.0007895514,0.001424856,0.000637577,0.00094057],"category_scores_gemma":[0.00149394,0.0003390253,0.0007674434,0.000710059,0.0003291828,0.0009985694,0.0007769394,0.0004769621,0.000102028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001409819,"about_ca_system_score_gemma":0.00155948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1377957,"about_ca_topic_score_gemma":0.07987152,"domain_scores_codex":[0.9996672,0.0001085151,0.00002525034,0.0001104013,0.00002409857,0.00006464277],"domain_scores_gemma":[0.9993455,0.0003915943,0.00006765643,0.00004862818,0.0001091518,0.00003748524],"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":[0.0002293953,0.0001877656,0.1184398,0.00009314254,0.0002527713,0.0001560913,0.0001313317,0.85716,0.0008984779,0.0009549592,0.0005831427,0.02091301],"study_design_scores_gemma":[0.000009242726,0.00002446363,0.01719296,0.000004698499,0.00003508884,0.00001290583,0.00007871856,0.9821663,0.0001255944,0.0002541176,0.00008576038,0.00001009637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9771063,0.0002029459,0.02144432,0.0001365239,0.00001465517,0.0000171952,0.0004155099,0.00006820806,0.0005943054],"genre_scores_gemma":[0.9952443,0.00007490977,0.003220938,0.00001583725,0.000006299579,0.0000268714,0.0005586105,0.000006459839,0.0008457062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1377957,"threshold_uncertainty_score":0.2739874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02902381335995095,"score_gpt":0.2633586905245581,"score_spread":0.2343348771646071,"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."}}