{"id":"W2952718687","doi":"10.3354/meps13029","title":"Fish population growth in the Gulf of St Lawrence: effects of climate, fishing and predator abundance","year":2019,"lang":"en","type":"article","venue":"Marine Ecology Progress Series","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Fishing; Capelin; Population; Fishery; Demersal fish; Fish stock; Predation; Herring; Pelagic zone; Population growth; Overexploitation; Demersal zone; Apex predator; Climate change; Forage fish; Trophic cascade; Fisheries science; Ecology; Biology; Predator; Fisheries management; Fish <Actinopterygii>; Demography","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":[0.0003302683,0.0001236054,0.00009828639,0.0003360658,0.000214633,0.0003177823,0.0001997928,0.0001465267,0.0003041093],"category_scores_gemma":[0.0007618836,0.00009788262,0.0001702963,0.0003640435,0.000215411,0.0002436304,0.0002897804,0.0001507335,0.00009105663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001452532,"about_ca_system_score_gemma":0.0007586003,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2777907,"about_ca_topic_score_gemma":0.5083366,"domain_scores_codex":[0.9998987,0.00001664375,0.000009404142,0.00002337857,0.00003103106,0.00002083088],"domain_scores_gemma":[0.9995152,0.00009371485,0.0001798605,0.00001872136,0.0001390844,0.00005347314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003567281,0.00001081552,0.9953849,0.000009081687,0.00002331551,0.00004073535,0.0001642764,0.0006946278,0.000833739,0.00002391725,0.00007502889,0.00270407],"study_design_scores_gemma":[0.000001423344,0.00001857552,0.9981996,0.000003176031,0.00000663485,0.00002568264,0.0001522145,0.001367717,0.00009862586,0.00001722232,0.0001066116,0.000002452976],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997079,0.00002558106,0.00003777946,0.00001815445,5.739255e-7,7.069457e-7,0.00007267752,0.000001834916,0.0001347613],"genre_scores_gemma":[0.9995403,0.00003883361,0.00007220051,0.000008260728,9.171254e-7,0.000001572193,0.0001545766,8.770272e-7,0.0001824604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7222093,"threshold_uncertainty_score":0.5523476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005245138474859683,"score_gpt":0.230688161025113,"score_spread":0.2254430225502533,"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."}}