{"id":"W2803062753","doi":"10.1002/fsh.10031","title":"Social Media for Fisheries Science and Management Professionals: How to Use It and Why You Should","year":2018,"lang":"en","type":"article","venue":"Fisheries","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Social media; Public relations; Fisheries management; Business; Resource (disambiguation); Natural resource; Political science; Fishing; Computer science","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01339317,0.0005336269,0.0004734191,0.002426003,0.006363459,0.013329,0.0008428523,0.005275027,0.01314484],"category_scores_gemma":[0.03503122,0.0004197393,0.0004382594,0.001707601,0.006009255,0.02073757,0.004788618,0.004925791,0.00575468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001821069,"about_ca_system_score_gemma":0.004490301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004075327,"about_ca_topic_score_gemma":0.009292556,"domain_scores_codex":[0.991887,0.004964029,0.0003781263,0.0002667181,0.001930397,0.0005735966],"domain_scores_gemma":[0.971513,0.01740205,0.001544846,0.0007844875,0.0049345,0.003821105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007735161,0.0003077643,0.01110508,0.002001269,0.0000347477,0.0005136353,0.06001557,0.00009067811,0.001766178,0.02398554,0.2416764,0.6584259],"study_design_scores_gemma":[0.000035387,0.0002242698,0.01287416,0.01087868,0.00005416915,0.000760799,0.1546622,0.0005022009,0.001122468,0.03660056,0.7821261,0.0001590381],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03343984,0.03388302,0.006453297,0.8338475,0.0046533,0.000230378,0.0001609749,0.000350467,0.08698127],"genre_scores_gemma":[0.5910575,0.1186304,0.03570003,0.1773228,0.009471211,0.001214864,0.0003008587,0.0005207581,0.06578161],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.986671,"threshold_uncertainty_score":0.07083064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09986199965653068,"score_gpt":0.3437410455298335,"score_spread":0.2438790458733028,"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."}}