{"id":"W4398478569","doi":"10.7910/dvn/ohwwnr/khb2qe","title":"07 HyenaPhotopicLumAdjust-DSC159ZebraModelGrey_Sobel_thr0.3.png","year":2016,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"ZEBRA (computer); Sobel operator; Zoology; Geography; Biology; Cartography; Art; Artificial intelligence; Computer science; Image processing; Edge detection; Operating system","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005681239,0.003453061,0.001502685,0.002519063,0.0008230626,0.002514393,0.003389909,0.002066407,0.1852495],"category_scores_gemma":[0.002526324,0.001032669,0.001582603,0.003511488,0.00046326,0.002085498,0.002818848,0.00145967,0.2721092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001114005,"about_ca_system_score_gemma":0.001555446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0209082,"about_ca_topic_score_gemma":0.04693408,"domain_scores_codex":[0.9994454,0.00006598562,0.00004052139,0.0001872154,0.000132,0.0001288906],"domain_scores_gemma":[0.9992244,0.0001214615,0.00006408025,0.0002868752,0.0001968699,0.0001062057],"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":[0.0000471085,0.00001213369,0.0004225854,0.0003363783,0.00002117601,0.00001320566,0.00001377979,0.0001926955,0.0001157117,0.0002790419,0.9969285,0.001617636],"study_design_scores_gemma":[0.000206825,0.00001256703,0.001900462,0.000137607,0.00001951278,0.00003926154,0.00005607841,0.0005720177,0.0006719306,0.001229362,0.9951258,0.00002858831],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001154525,0.00004801865,0.00008042546,0.00003740791,0.0000225171,0.000007405435,0.9965062,0.002215984,0.0009665314],"genre_scores_gemma":[0.0003302765,0.00003754604,0.0002401415,0.0000313934,0.00000559742,0.00002413064,0.9981228,0.0003851378,0.0008231017],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8147506,"threshold_uncertainty_score":0.6197212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01282543284110769,"score_gpt":0.2301897723621986,"score_spread":0.2173643395210909,"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."}}