{"id":"W4225575939","doi":"10.1139/facets-2021-0112","title":"Evaluating the benefits and risks of social media for wildlife conservation","year":2022,"lang":"en","type":"article","venue":"FACETS","topic":"Animal and Plant Science Education","field":"Psychology","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; University of Ottawa; Carleton University","funders":"University of Florida","keywords":"Social media; Misinformation; Wildlife; Public relations; Business; Tourism; Wildlife conservation; Misconduct; Political science; Environmental planning; Internet privacy; Environmental resource management; Geography; Economics; Ecology; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006138553,0.00002894184,0.00004718854,0.00001602952,0.0002965102,0.000005185107,0.0000684133,0.00001620325,0.0003750064],"category_scores_gemma":[0.0001118511,0.00002234277,0.00001336546,0.00006965984,0.00003623404,0.00002277963,0.00002045823,0.0000492015,0.000003991372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006955436,"about_ca_system_score_gemma":0.00002739007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007784005,"about_ca_topic_score_gemma":0.00002277724,"domain_scores_codex":[0.99956,0.00007523453,0.00008552238,0.00008758641,0.000117133,0.00007453205],"domain_scores_gemma":[0.9994555,0.0003828581,0.00008158624,0.0000412942,0.00002813071,0.0000106473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0006644178,0.0002897756,0.1540222,0.00003372514,0.00006975164,3.530227e-7,0.253043,0.0003309466,0.007846536,0.1561102,0.2024301,0.225159],"study_design_scores_gemma":[0.0004017215,0.0002846408,0.971377,0.000002611133,0.00002196637,0.000005955053,0.01151252,0.001355627,0.00005025034,0.001637615,0.01328098,0.00006915606],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946642,0.0001186229,0.00002302949,0.004000132,0.0005033867,0.0001604617,0.000107378,0.000005968199,0.0004168226],"genre_scores_gemma":[0.9990827,0.000001292397,0.0001042048,0.0004507452,0.00009111875,0.00007460243,0.00003255456,0.000002295364,0.0001605129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8173547,"threshold_uncertainty_score":0.4106057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3360177116606757,"score_gpt":0.4515077931244005,"score_spread":0.1154900814637249,"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."}}