{"id":"W3005901815","doi":"10.1145/3383653.3383667","title":"The Eighth ACM SIGSPATIAL International Workshop on Analysis for Big Spatial Data","year":2020,"lang":"en","type":"article","venue":"SIGSPATIAL Special","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Esri (Canada)","funders":"","keywords":"Big data; Data science; Realm; Computer science; White paper; Geography; Data mining","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001141892,0.0002354257,0.0003693899,0.0001871194,0.00214952,0.0005110432,0.002659183,0.0001594695,0.000517729],"category_scores_gemma":[0.006543843,0.000184162,0.0002971172,0.001083414,0.0003771312,0.0003124309,0.0006697202,0.0002327544,0.0001626964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001067568,"about_ca_system_score_gemma":0.0002249782,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003691669,"about_ca_topic_score_gemma":0.07013898,"domain_scores_codex":[0.9967503,0.0001960943,0.0006642685,0.0005076552,0.001347358,0.0005343186],"domain_scores_gemma":[0.996794,0.001413777,0.0004095973,0.0007537096,0.0004104936,0.0002184567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002595198,0.0002499553,0.04591024,0.00003278906,0.005308083,0.00001240857,0.07775734,0.001139695,0.00002240639,0.08611151,0.2950728,0.4857876],"study_design_scores_gemma":[0.0007499097,0.00008284656,0.00746916,0.00000952152,0.0001971127,1.086624e-7,0.004823413,0.001931087,0.00001209695,0.0006985117,0.9837437,0.0002825185],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01991745,0.0002693795,0.1853493,0.3763064,0.0676019,0.008272376,0.006074196,0.001079069,0.33513],"genre_scores_gemma":[0.9303745,0.0001145482,0.0002846063,0.001247299,0.06676237,0.0001043122,0.0005961044,0.00002077018,0.0004955073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.910457,"threshold_uncertainty_score":0.9991496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1376918085424101,"score_gpt":0.3515859207313645,"score_spread":0.2138941121889545,"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."}}