{"id":"W4398335890","doi":"10.7910/dvn/ohwwnr/edatlr","title":"11 LionScotopicLuminanceAdjusted-DSC006ZebraGroupPlains_Sobel_thr0.15.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; Art; Computer science; Artificial intelligence; Paleontology; 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":[0.0006328944,0.003418304,0.001643435,0.003348612,0.0009873252,0.002533185,0.003793547,0.002207624,0.1554217],"category_scores_gemma":[0.003479865,0.0009293517,0.001749381,0.004449412,0.0004660928,0.001955675,0.002896291,0.001656845,0.2309367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001293328,"about_ca_system_score_gemma":0.001942154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02350901,"about_ca_topic_score_gemma":0.06257308,"domain_scores_codex":[0.9992418,0.00009280317,0.00006170338,0.0002584796,0.0001800406,0.0001651922],"domain_scores_gemma":[0.9989508,0.0001887986,0.0001058149,0.000312547,0.0003104195,0.0001314113],"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":[0.00004855144,0.00001385499,0.0007522865,0.0004077313,0.0000223368,0.00001685495,0.00001322413,0.0001553676,0.0001094556,0.0002450997,0.996384,0.001831245],"study_design_scores_gemma":[0.0001940507,0.00001546849,0.002819855,0.0002165943,0.00002561818,0.00005589248,0.00006964514,0.0004326758,0.000527168,0.001104543,0.9945088,0.00002970463],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001409144,0.00007352255,0.00006268347,0.00003683489,0.00002281275,0.000007338648,0.9976809,0.001128904,0.0008460051],"genre_scores_gemma":[0.0003429966,0.00004578151,0.0002216943,0.00003827932,0.000006578459,0.00002950936,0.9981995,0.0002192802,0.0008963909],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8445783,"threshold_uncertainty_score":0.5199375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01030710060270425,"score_gpt":0.2250611253571889,"score_spread":0.2147540247544847,"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."}}