{"id":"W4398259176","doi":"10.7910/dvn/ohwwnr/sqwhmh","title":"11 ZebraScotopicLuminanceAdjusted-DSC006ZebraGroupPlains_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; Predation; Zoology; Biology; Cartography; Art; Geography; Computer science; Artificial intelligence; Ecology; Image processing; Image (mathematics); 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":[0.0005783872,0.003098018,0.00158683,0.003204513,0.0009574928,0.002395344,0.003668692,0.002028333,0.1389226],"category_scores_gemma":[0.003262972,0.000937504,0.001706978,0.004426403,0.0004946202,0.001759624,0.002720977,0.001675474,0.2247614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001157405,"about_ca_system_score_gemma":0.001750863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02212321,"about_ca_topic_score_gemma":0.0600641,"domain_scores_codex":[0.9992704,0.00008580246,0.00005732446,0.0002475355,0.0001773743,0.0001616706],"domain_scores_gemma":[0.9989888,0.0001799518,0.00009988619,0.0003083688,0.0003115331,0.0001114176],"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":[0.00005433,0.00001412361,0.0009054262,0.0004133138,0.00002637168,0.00001983975,0.00001509966,0.0002055799,0.000138611,0.0002693245,0.9959282,0.00200979],"study_design_scores_gemma":[0.0001862637,0.00001348339,0.003393607,0.000196471,0.00002783592,0.00006030942,0.00007741697,0.0004434937,0.0006342705,0.00121102,0.9937239,0.00003189372],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001708115,0.00007071415,0.00008337752,0.00003283077,0.00002265529,0.000006934123,0.9975045,0.001250766,0.0008573739],"genre_scores_gemma":[0.000402455,0.00004094189,0.0002524274,0.00002993254,0.000005399711,0.00002851866,0.9981427,0.0002307886,0.0008668469],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8610774,"threshold_uncertainty_score":0.4647424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009945684204945167,"score_gpt":0.2236073499528492,"score_spread":0.213661665747904,"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."}}