{"id":"W2734982386","doi":"10.1139/cjfas-2016-0426","title":"The Lobster Node of the CFRN: co-constructed and collaborative research on productivity, stock structure, and connectivity in the American lobster (<i>Homarus</i> <i>americanus</i>)","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Veterans Affairs Canada; Maritime Fishermen's Union; Guysborough County Inshore Fishermen's Association; Université de Moncton; Cégep de la Gaspésie et des Îles; Université Laval; Canadian Respiratory Research Network; Agriculture and Agri-Food Canada; Fisheries and Oceans Canada; University of Prince Edward Island; Saint John Regional Hospital; University of New Brunswick","funders":"Fisheries and Oceans Canada","keywords":"Homarus; American lobster; Fishery; Stock (firearms); Productivity; Fishing; Geography; Engineering research; General partnership; Fisheries management; Marine research; Business; Oceanography; Engineering; Economics; Biology; Crustacean; Economic growth","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.01058007,0.000258665,0.0004086436,0.002271331,0.01067954,0.006423177,0.001340203,0.0008215714,0.001642688],"category_scores_gemma":[0.01175253,0.0002615332,0.0002782457,0.003358369,0.007813874,0.003102192,0.008248048,0.001444575,0.0001764051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03478098,"about_ca_system_score_gemma":0.1021934,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.86843,"about_ca_topic_score_gemma":0.9625792,"domain_scores_codex":[0.995842,0.0014255,0.0001110579,0.0005555748,0.0009592516,0.001106519],"domain_scores_gemma":[0.9887683,0.003393268,0.0008043781,0.0006189728,0.003189294,0.003225767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001860144,0.0001144729,0.3037217,0.0006675402,0.0001323406,0.001991221,0.3837864,0.000936359,0.002399947,0.059335,0.01717059,0.2295585],"study_design_scores_gemma":[0.00002623184,0.0001716918,0.1940104,0.001426225,0.0001716445,0.0005043065,0.5700969,0.0008030285,0.001774774,0.008691172,0.2222143,0.0001094095],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8757717,0.01039621,0.006160459,0.02328009,0.000472934,0.0005101346,0.0006892689,0.00009053371,0.08262872],"genre_scores_gemma":[0.972665,0.004698302,0.008001838,0.001618036,0.00003765599,0.0001374843,0.0004045666,0.00003711085,0.01239999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.13157,"threshold_uncertainty_score":0.2646897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03645890607654571,"score_gpt":0.3054305225109508,"score_spread":0.268971616434405,"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."}}