{"id":"W4285589627","doi":"10.1111/cobi.13976","title":"Scientific contributions of citizen science applied to rare or threatened animals","year":2022,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Ministère des Ressources naturelles et des Forêts; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Liber Ero Foundation","keywords":"Citizen science; Threatened species; Multidisciplinary approach; Conservation science; Identification (biology); Political science; Grey literature; Public relations; Environmental resource management; Environmental planning; Geography; Habitat; Ecology; Biology; Environmental science; MEDLINE","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":[0.1642964,0.001171627,0.001676592,0.03956831,0.00439203,0.01294076,0.00189698,0.002625276,0.006658597],"category_scores_gemma":[0.4238799,0.0009536003,0.001778128,0.04113343,0.005859311,0.009632333,0.0182447,0.002658805,0.001758049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004357476,"about_ca_system_score_gemma":0.01578963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002110328,"about_ca_topic_score_gemma":0.003812244,"domain_scores_codex":[0.7650174,0.1538259,0.0166844,0.009402396,0.05087191,0.00419795],"domain_scores_gemma":[0.3018292,0.5203493,0.06140097,0.03788855,0.06454924,0.01398263],"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":[0.0003076259,0.0002181266,0.221583,0.01493532,0.0013265,0.001318902,0.05517432,0.001324111,0.003062708,0.0141774,0.01970425,0.6668677],"study_design_scores_gemma":[0.0001689991,0.0006086245,0.3298315,0.0205924,0.002092103,0.003715923,0.05756896,0.003579132,0.004486036,0.06568376,0.5113019,0.0003707738],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5565033,0.06980347,0.04760414,0.07574767,0.0067254,0.003360101,0.008660364,0.0007825468,0.2308131],"genre_scores_gemma":[0.8992344,0.02937528,0.04940097,0.005276222,0.003346967,0.001756524,0.001938378,0.0004140448,0.009257082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1642964,"threshold_uncertainty_score":0.8688928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04430069307131385,"score_gpt":0.2958095044520908,"score_spread":0.2515088113807769,"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."}}