{"id":"W6976708860","doi":"10.6068/dp16b4c0ed9c083","title":"TREND: Xignite. Worldwide Stock Market Prices by Region: Stock Daily High | Economic Regions/Exchanges: Warsaw Stock Exchange | Exchange: Warsaw Stock Exchange, . Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 016-004-003","year":2019,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stock exchange; Stock (firearms); Cash; Stock market; Market maker; Stock market bubble","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":[],"consensus_categories":[],"category_scores_codex":[0.001190051,0.002415519,0.001500549,0.003471214,0.0006695687,0.003239193,0.003204534,0.002180305,0.1188579],"category_scores_gemma":[0.005812906,0.0007501914,0.00141146,0.0055655,0.0003049754,0.001992585,0.002219687,0.00244951,0.1879865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001164694,"about_ca_system_score_gemma":0.001623683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0120807,"about_ca_topic_score_gemma":0.02128159,"domain_scores_codex":[0.9993473,0.00009608409,0.00007690386,0.000227813,0.000139921,0.000111922],"domain_scores_gemma":[0.9983495,0.0003177744,0.0002391145,0.0004834592,0.0004064385,0.0002036506],"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":[0.00002426109,0.00001313743,0.0007331495,0.0001967559,0.00001734036,0.00001020029,0.000008249172,0.0001460814,0.00003713715,0.0002257585,0.9972409,0.001347175],"study_design_scores_gemma":[0.0004068231,0.00003510705,0.007520151,0.0003419819,0.00004631409,0.00006416586,0.0000773991,0.001205866,0.0003096487,0.001896143,0.988052,0.00004445351],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009499576,0.00002627087,0.0000586324,0.0000589113,0.00002258868,0.00001133471,0.9989225,0.0003839269,0.0004207822],"genre_scores_gemma":[0.0002731174,0.00002978703,0.0002267017,0.00004544891,0.00001287029,0.00008964963,0.9987103,0.0000727092,0.0005394444],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1188579,"threshold_uncertainty_score":0.3976191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04682340472195266,"score_gpt":0.2759761937827966,"score_spread":0.229152789060844,"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."}}