{"id":"W4398566722","doi":"10.7910/dvn/ohwwnr/see8gw","title":"09 ZebraPhotopicLuminanceAdjusted-DSC006ZebraGroupPlains_Sobel_thr0.3.png","year":2016,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Sobel operator; Computer science; Artificial intelligence; Image processing; Image (mathematics)","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":[0.0007986557,0.0030715,0.002209014,0.003561629,0.001176094,0.003050514,0.004044111,0.002430166,0.1892047],"category_scores_gemma":[0.003557419,0.00127031,0.001521716,0.004905308,0.0005191623,0.001982939,0.00307368,0.001685917,0.2496711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001149229,"about_ca_system_score_gemma":0.001799531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0134432,"about_ca_topic_score_gemma":0.02988626,"domain_scores_codex":[0.999307,0.0000853599,0.00004895462,0.0002622709,0.0001591615,0.0001372549],"domain_scores_gemma":[0.9989685,0.0002617982,0.0001218807,0.0003277875,0.0001941365,0.0001259522],"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":[0.0001472049,0.00001841989,0.001366703,0.001448985,0.00007387914,0.00003570151,0.00003601145,0.0003024891,0.0005171784,0.0007323473,0.9924648,0.002856375],"study_design_scores_gemma":[0.0002564738,0.0000137413,0.003160376,0.0002553475,0.00005130636,0.00006361899,0.00004939112,0.0002555005,0.0008942912,0.00166998,0.9932909,0.00003905595],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001420611,0.0001047049,0.00009836999,0.00002938062,0.00001479581,0.000004884829,0.9970114,0.00181238,0.0007819398],"genre_scores_gemma":[0.0005698738,0.00008628421,0.0003303974,0.00004909926,0.000005286178,0.00003511453,0.9975526,0.0005342679,0.0008371148],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8107953,"threshold_uncertainty_score":0.6329527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007604304707317349,"score_gpt":0.2546183094670965,"score_spread":0.2470140047597792,"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."}}