{"id":"W4360801527","doi":"10.5281/zenodo.7765343","title":"8 Types Of Bears In Contrast - Identification Information","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Contrast (vision); Identification (biology); Computer science; Artificial intelligence; Biology; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004048096,0.0003822974,0.0002622178,0.001432727,0.0007513078,0.0006084757,0.0005915894,0.0004102098,0.04547816],"category_scores_gemma":[0.001272119,0.0001682408,0.0003075448,0.00141602,0.0002181647,0.0008821133,0.0008335317,0.0002747822,0.009243408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003265516,"about_ca_system_score_gemma":0.0002835206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002654854,"about_ca_topic_score_gemma":0.00452343,"domain_scores_codex":[0.9993864,0.0000575639,0.00006140029,0.0001495351,0.0002325696,0.0001124891],"domain_scores_gemma":[0.9992411,0.0001859195,0.0001649888,0.0001954858,0.0001604926,0.00005210789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002182112,0.0004512671,0.3635321,0.0007622519,0.0001507389,0.003876616,0.003326494,0.001539533,0.01656616,0.0380244,0.1327919,0.4367965],"study_design_scores_gemma":[0.0001087116,0.0003259318,0.3504891,0.0003962274,0.0002532155,0.008738829,0.002465791,0.003746969,0.0165881,0.01070021,0.6060541,0.0001328268],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5750261,0.002071561,0.01308752,0.001111412,0.0007233896,0.0003946207,0.05772272,0.0009852576,0.3488775],"genre_scores_gemma":[0.8332707,0.0009147167,0.01305001,0.0006197785,0.0003751866,0.0002681476,0.04661531,0.0001730079,0.1047131],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04547816,"threshold_uncertainty_score":0.1521396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02583748028500684,"score_gpt":0.2420993526971,"score_spread":0.2162618724120931,"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."}}