{"id":"W4393611632","doi":"10.5281/zenodo.7224905","title":"Banding Patches Dataset with Corresponding Banded and Pristine Pairs","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Geography; Geology; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0004767219,0.003105325,0.001773796,0.002383075,0.0008157778,0.001280778,0.002426886,0.002071497,0.01981606],"category_scores_gemma":[0.001566892,0.0005593861,0.001494188,0.003166424,0.000523373,0.0008111171,0.00149491,0.001273613,0.03144353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007819929,"about_ca_system_score_gemma":0.001034708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01724606,"about_ca_topic_score_gemma":0.03604889,"domain_scores_codex":[0.999112,0.00008122984,0.00006902598,0.0003306088,0.0002509207,0.0001561678],"domain_scores_gemma":[0.9994833,0.00008351966,0.00003933944,0.0002053613,0.0001283716,0.00006012667],"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":[0.0004955644,0.0002512519,0.002676949,0.001279961,0.0001820824,0.0002578605,0.00004737846,0.001476785,0.003377067,0.0004839676,0.9624443,0.02702676],"study_design_scores_gemma":[0.0008396844,0.0002500012,0.04568537,0.0004591439,0.0002992417,0.001898305,0.000393011,0.01242076,0.009829493,0.002850081,0.9249141,0.0001609736],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.007365493,0.0008307971,0.001328018,0.0001353317,0.0001635401,0.0001368836,0.9833573,0.003644012,0.003038569],"genre_scores_gemma":[0.003652571,0.0001048242,0.00145311,0.00003949269,0.00001291723,0.00008724081,0.9936552,0.0001002457,0.0008944247],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01981606,"threshold_uncertainty_score":0.06629133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0408078492081116,"score_gpt":0.2823318850304613,"score_spread":0.2415240358223497,"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."}}