{"id":"W2911498471","doi":"10.3354/meps12873","title":"Implications of extremely high recruitment: crowding and reduced growth within spatial closures","year":2019,"lang":"en","type":"article","venue":"Marine Ecology Progress Series","topic":"Marine Bivalve and Aquaculture Studies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scallop; Crowding; Fishing; Fishery; Ecology; Biology; Population; Geography; Demography; Sociology","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":[0.001042816,0.0001944438,0.0002509077,0.0005710347,0.0007581146,0.0006186306,0.000491296,0.0004216629,0.001739484],"category_scores_gemma":[0.005280402,0.0001395647,0.0003194505,0.0003574472,0.001267351,0.0005145611,0.001033431,0.0004262597,0.0001112215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007697758,"about_ca_system_score_gemma":0.0006292099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02368245,"about_ca_topic_score_gemma":0.04695237,"domain_scores_codex":[0.9992342,0.0001329041,0.00005969277,0.0002467203,0.0001302371,0.0001962641],"domain_scores_gemma":[0.9948577,0.0008465802,0.002052188,0.0004244444,0.0003305144,0.00148865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003555699,0.00008917532,0.9717537,0.00006201975,0.00007628646,0.001108477,0.001449273,0.002387342,0.01092818,0.0006283585,0.0005459323,0.01061569],"study_design_scores_gemma":[0.000003224328,0.00006934191,0.9967361,0.00001166667,0.000009315526,0.0002277338,0.0009385308,0.001178896,0.0003168255,0.0002569965,0.000243298,0.000007974666],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988233,0.00006520488,0.0003396331,0.00009209895,0.000006563283,0.000005172847,0.00007878985,0.000007667095,0.000581547],"genre_scores_gemma":[0.9996469,0.00001422568,0.0001350996,0.00002009647,0.000003381268,0.000003414182,0.00003975349,0.000002307778,0.0001349098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02368245,"threshold_uncertainty_score":0.04708922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01804574428592221,"score_gpt":0.2553132916682546,"score_spread":0.2372675473823324,"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."}}