{"id":"W6961288751","doi":"10.14288/1.0443241","title":"View of Vancouver","year":2024,"lang":"en","type":"other","venue":"Open Collections","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lantern; MAGIC (telescope); Ridiculous; Government (linguistics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00173345,0.000116951,0.0003174396,0.0004642039,0.0002714059,0.002672265,0.00179745,0.00006696604,0.04508545],"category_scores_gemma":[0.000441223,0.00008606316,0.0001075542,0.0037952,0.0000625528,0.00006433416,0.001436151,0.00009945622,0.00203121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002579744,"about_ca_system_score_gemma":0.0001158623,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01052269,"about_ca_topic_score_gemma":0.03645321,"domain_scores_codex":[0.997974,0.00008082152,0.0004078562,0.0006941274,0.0007197935,0.000123386],"domain_scores_gemma":[0.9981576,0.0001600219,0.0002154743,0.001332673,0.0000849144,0.00004936893],"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":[0.000001150196,0.00003023156,4.366392e-7,0.00001209475,0.00003710561,0.000002239677,0.00001798982,0.000005859272,1.435165e-7,0.0002040602,0.9907907,0.00889805],"study_design_scores_gemma":[0.00006921945,0.00001474214,8.218725e-7,0.0001497935,0.00002957329,9.283571e-7,0.0001527578,0.0001454482,0.000001639834,0.01141669,0.9879242,0.00009414278],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[3.260164e-8,0.0003791304,0.002147884,0.00006003261,0.008004121,0.0004167479,0.0002573918,0.00006492164,0.9886698],"genre_scores_gemma":[0.000006231984,0.00002274381,0.00168969,0.00004698821,0.0001119727,0.00002577487,0.000005989691,0.00008144463,0.9980091],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04305424,"threshold_uncertainty_score":0.9987458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1288711368934378,"score_gpt":0.4078443972363049,"score_spread":0.2789732603428671,"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."}}