{"id":"W7095317716","doi":"","title":"Estimation of Stock Reproductive Potential: History and Challenges for Canadian Atlantic Gadoid Stock Assessments","year":2015,"lang":"en","type":"article","venue":"","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Groundfish; Stock (firearms); Population; Stock assessment; Estimation; Fisheries management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005884195,0.0004016341,0.0004596543,0.00356644,0.001283744,0.001693778,0.001768226,0.0003362181,0.001064523],"category_scores_gemma":[0.01358913,0.0002305999,0.0003489399,0.003463677,0.0006649487,0.001350353,0.001130255,0.0005862913,0.0002451707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00772514,"about_ca_system_score_gemma":0.01084794,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8602973,"about_ca_topic_score_gemma":0.9366539,"domain_scores_codex":[0.9984366,0.0002663068,0.0001490193,0.0001555612,0.0008843493,0.000108083],"domain_scores_gemma":[0.9909166,0.001584097,0.0007430211,0.0003627149,0.006024983,0.0003685481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00005276138,0.00001757294,0.4881491,0.000281329,0.00006687753,0.0001225615,0.001184979,0.005436047,0.001321603,0.002179854,0.006091685,0.4950957],"study_design_scores_gemma":[0.00001304417,0.0001031061,0.9082587,0.0006811913,0.000102189,0.0002910254,0.004996873,0.04095726,0.001817542,0.004463893,0.03820394,0.0001112314],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7568138,0.03029302,0.11163,0.01857853,0.0002976985,0.0006110206,0.01243386,0.0008670678,0.06847492],"genre_scores_gemma":[0.8834606,0.007394272,0.1017998,0.0005295351,0.0000601607,0.0001044002,0.00245851,0.00006754367,0.004125001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1397027,"threshold_uncertainty_score":0.2810508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08448180901212457,"score_gpt":0.2867397811653868,"score_spread":0.2022579721532623,"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."}}