{"id":"W4205323682","doi":"10.32942/osf.io/uyqd3","title":"Dataset of seized wildlife and their intended uses","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wildlife Conservation Society Canada","funders":"University of Adelaide","keywords":"Wildlife; Wildlife trade; Taxon; The Internet; Biosecurity; Geography; Business; Social media; Internet privacy; World Wide Web; Computer science; Biology; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.0006829675,0.0009641318,0.000781576,0.004336128,0.0007524395,0.001309159,0.001156487,0.001422017,0.01011583],"category_scores_gemma":[0.00376224,0.0003361846,0.0008472125,0.005759184,0.0005212093,0.001293154,0.001860436,0.001200628,0.01574876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008512914,"about_ca_system_score_gemma":0.001448734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01061418,"about_ca_topic_score_gemma":0.02022023,"domain_scores_codex":[0.998777,0.0001455397,0.0002418,0.000332085,0.0003427204,0.0001608799],"domain_scores_gemma":[0.9977597,0.0005049337,0.0004335612,0.0005438016,0.0005575446,0.0002003481],"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":[0.000714319,0.0003126644,0.09576817,0.0033124,0.0002498291,0.0008446212,0.0005762717,0.003712593,0.004407185,0.003995475,0.8365916,0.04951495],"study_design_scores_gemma":[0.0001339596,0.00008572999,0.1224136,0.0006165717,0.00008127526,0.0009132034,0.0009065481,0.003576477,0.002205579,0.002023939,0.8669541,0.00008900458],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01007764,0.000275943,0.0005059884,0.0001255833,0.0000530614,0.00004611079,0.9865522,0.0003109125,0.002052585],"genre_scores_gemma":[0.006724475,0.0001449706,0.001407492,0.00005486192,0.00001322474,0.00007558292,0.9906541,0.0000308503,0.0008946019],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01061418,"threshold_uncertainty_score":0.03384084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03568122158615034,"score_gpt":0.2940732776734816,"score_spread":0.2583920560873313,"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."}}