{"id":"W2944909484","doi":"10.1139/facets-2019-0022","title":"Correction: Impacts of hypoxia on estuarine macroinvertebrate assemblages across a regional nutrient gradient","year":2019,"lang":"en","type":"article","venue":"FACETS","topic":"Marine Biology and Ecology Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; Canadian Water Network; University of Prince Edward Island","funders":"","keywords":"Hypoxia (environmental); Nutrient; Environmental science; Estuary; Ecology; Oceanography; Geography; Biology; Geology; Chemistry; Oxygen","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003523745,0.0001172337,0.0001997249,0.00005987086,0.0001157601,0.00001536319,0.0001867104,0.0001135887,0.003636581],"category_scores_gemma":[0.00006325877,0.0000889634,0.00005943312,0.0001613105,0.0001090946,0.00007610241,0.00003069788,0.0002157448,0.001969501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007649705,"about_ca_system_score_gemma":0.00005246245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001257135,"about_ca_topic_score_gemma":0.004611141,"domain_scores_codex":[0.9988951,0.00008821581,0.0001700031,0.0002637099,0.0001825369,0.000400449],"domain_scores_gemma":[0.9993386,0.0002029547,0.00007933952,0.0002099558,0.00004634126,0.0001228653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002312732,0.00005157549,0.9843551,0.00001569416,0.00002658313,0.000008833843,0.0001276417,0.0002216979,0.0001922735,0.00006082058,0.01236067,0.002347854],"study_design_scores_gemma":[0.0004420158,0.0008979494,0.9890463,0.00001592672,0.000002814073,0.00004064125,0.00009726478,0.002934769,0.001041423,0.0001658128,0.005215317,0.00009976273],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905015,0.00007782737,0.000001845468,0.0004463111,0.001223132,0.000209206,0.00001459657,0.00002320098,0.007502333],"genre_scores_gemma":[0.9941952,0.0000700504,0.00001282252,0.0002527041,0.00005330341,0.000001665391,0.00009504447,0.000002397725,0.005316807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007145355,"threshold_uncertainty_score":0.9988076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01991859525290965,"score_gpt":0.2664316063986389,"score_spread":0.2465130111457293,"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."}}