{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002277252,0.0007479741,0.0003984793,0.001616036,0.007757328,0.006068591,0.0006649329,0.001517858,0.415713],"category_scores_gemma":[0.000766566,0.0004263497,0.0003471131,0.003271679,0.0006839653,0.001529798,0.001900286,0.002475072,0.1300196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006379041,"about_ca_system_score_gemma":0.007871674,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7130939,"about_ca_topic_score_gemma":0.9319443,"domain_scores_codex":[0.9996933,0.0000225051,0.000006781491,0.00003860145,0.0001563925,0.00008244169],"domain_scores_gemma":[0.9993774,0.00002682266,0.000009307179,0.00002448488,0.0003580659,0.0002039177],"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":[0.00001495566,0.00000484657,0.0001856124,0.00004709198,0.000002008124,0.00008192351,0.000100577,0.00004043967,0.00008043893,0.002168016,0.9801745,0.01709944],"study_design_scores_gemma":[0.000001512993,0.000001365827,0.0004116029,0.00004423485,0.000001376513,0.0000242369,0.0002490099,0.00001142529,0.00003208183,0.0002093607,0.9990103,0.000003464553],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001221969,0.008265157,0.000426837,0.007814867,0.004548071,0.00004645255,0.00595704,0.0004346572,0.9712849],"genre_scores_gemma":[0.003771981,0.002241468,0.0002675739,0.0007906495,0.0001865599,0.00001342944,0.001301389,0.0002109483,0.9912159],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7130939,"threshold_uncertainty_score":0.8334144,"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."}}