{"id":"W4398310685","doi":"10.7910/dvn/ohwwnr/c4rwro","title":"04 ZebraPhotopicLuminanceAdjusted-DSC039ZebraWoodlands_Sobel_thr0.3.png","year":2016,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Astronomical Observations and Instrumentation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Sobel operator; Computer science; Artificial intelligence; Image processing","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00007895684,0.0003583973,0.0003474568,0.000153795,0.00008380035,0.0000756114,0.000464208,0.0002715834,0.01620008],"category_scores_gemma":[0.00002510721,0.0003196558,0.0001163143,0.0001294009,0.00006455945,0.0005390318,0.0001258355,0.0002861771,0.04328147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001738243,"about_ca_system_score_gemma":0.00004022981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009804238,"about_ca_topic_score_gemma":0.00005894408,"domain_scores_codex":[0.9986559,0.00002243493,0.0004155268,0.0003306655,0.0001963472,0.0003791803],"domain_scores_gemma":[0.9987759,0.0000402613,0.0001041135,0.0009186736,0.00003361351,0.0001274176],"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":[0.000006313664,0.00001832091,0.00003365464,0.00008888721,0.00006655278,0.000006924198,0.000004607192,0.00004594706,0.00009111174,0.00004567957,0.9974114,0.002180623],"study_design_scores_gemma":[0.0005318789,0.00002806437,0.0002713896,0.0001325139,0.00006477677,0.000003359391,0.00001304942,0.0002257167,0.0002135194,0.00002211791,0.9981074,0.0003862381],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009495189,0.000002323581,0.0006011145,0.000004235797,0.001248442,0.0002496437,0.9963597,0.0001774182,0.000407598],"genre_scores_gemma":[0.0003240373,0.0004184545,0.0003953004,0.00009288471,0.0004486513,0.00005765021,0.9980575,0.00004265638,0.0001628508],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02708139,"threshold_uncertainty_score":0.9999256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01084951519887345,"score_gpt":0.2058206469892515,"score_spread":0.194971131790378,"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."}}