{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.001328395,0.0001226933,0.0001667198,0.00007469564,0.001992792,0.001131922,0.0002283787,0.00008660246,0.00003140352],"category_scores_gemma":[0.005473341,0.000113599,0.0000249473,0.000393418,0.003000541,0.001069113,0.0002098215,0.0000579924,0.000002494812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005591108,"about_ca_system_score_gemma":0.0001298335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001164626,"about_ca_topic_score_gemma":0.003335539,"domain_scores_codex":[0.9984077,0.00007230452,0.0001197055,0.0003384039,0.000627329,0.0004345143],"domain_scores_gemma":[0.9988014,0.0004868327,0.0000529149,0.00009109384,0.0003623927,0.0002053752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001436974,0.00004948365,0.01283052,0.00009931219,0.00002521762,0.000002918319,0.2071667,3.53042e-9,0.0000324332,0.03446578,0.6733032,0.07188073],"study_design_scores_gemma":[0.0001516682,0.00006124999,0.02804921,0.0000475861,0.00001265446,1.890842e-7,0.04885909,0.00000149822,0.00003237269,0.003111507,0.9194931,0.0001798305],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7168503,0.00004160749,0.00006517387,0.2024936,0.001888242,0.001114195,0.00006606126,0.0001912205,0.07728957],"genre_scores_gemma":[0.9816011,0.00007090252,0.002487373,0.004022119,0.001109904,0.000186168,0.000004781529,0.00002088615,0.0104968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2647507,"threshold_uncertainty_score":0.999905,"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."}}