{"id":"W4294898133","doi":"10.1002/fsh.10831","title":"Citizen Science Surveys Provide Novel Nearshore Data","year":2022,"lang":"en","type":"article","venue":"Fisheries","topic":"Marine Biology and Ecology Research","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parks Canada; University of Victoria; Fisheries and Oceans Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Liber Ero Foundation; Fisheries and Oceans Canada; Canadian Federation of University Women","keywords":"Citizen science; Data science; Geography; Fishery; Oceanography; Environmental resource management; Environmental science; Computer science; Biology; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003551744,0.0003671005,0.0004981965,0.004085021,0.0009002176,0.003053799,0.0007088694,0.00096473,0.00759089],"category_scores_gemma":[0.01345294,0.0004504279,0.000300602,0.007338268,0.0005199203,0.003355245,0.002999746,0.000825357,0.003453729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007203093,"about_ca_system_score_gemma":0.001888973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01556893,"about_ca_topic_score_gemma":0.05301419,"domain_scores_codex":[0.9949987,0.002153356,0.0004262273,0.0006578687,0.001474719,0.0002891489],"domain_scores_gemma":[0.9799008,0.006111948,0.003414388,0.004221306,0.005688967,0.0006627269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002145826,0.0002919047,0.4292637,0.001371893,0.0002518776,0.0007996454,0.007742492,0.002234593,0.007882326,0.01255766,0.06942452,0.4679647],"study_design_scores_gemma":[0.00005690341,0.0003091177,0.4254415,0.001475082,0.0001781125,0.001112653,0.03473863,0.008786819,0.005542263,0.0183668,0.5037759,0.0002162513],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5167337,0.002134803,0.1403499,0.008741091,0.0005258542,0.001181086,0.1313328,0.002192914,0.196808],"genre_scores_gemma":[0.7613122,0.002094045,0.1636311,0.001704831,0.0002515508,0.001018292,0.04897685,0.0003637763,0.02064727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01556893,"threshold_uncertainty_score":0.03095663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0894808506011979,"score_gpt":0.2721373195787152,"score_spread":0.1826564689775173,"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."}}