{"id":"W6960796219","doi":"10.1371/journal.pone.0288883.t003","title":"Descriptive statistics (actual data).","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preference; Contrast (vision); Stock market; Information asymmetry; Market liquidity; Stock (firearms); Prospect theory","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":[0.004135635,0.0009584356,0.001108644,0.005197158,0.0007291475,0.00124016,0.001555604,0.0007628335,0.2094553],"category_scores_gemma":[0.0419905,0.0002997115,0.0005343686,0.007304264,0.0005360119,0.001288968,0.00123757,0.001974671,0.04921069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009541151,"about_ca_system_score_gemma":0.002580947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003055784,"about_ca_topic_score_gemma":0.002744166,"domain_scores_codex":[0.9945168,0.0008886286,0.0009403559,0.0007440388,0.00252159,0.0003885414],"domain_scores_gemma":[0.9706421,0.01569958,0.003738507,0.002901561,0.006510563,0.0005077736],"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":[0.0006229847,0.0004401034,0.01527777,0.002921825,0.00009087202,0.0002689039,0.0009556363,0.0007743947,0.0006499458,0.006099021,0.839242,0.1326566],"study_design_scores_gemma":[0.0001704902,0.0006972124,0.09034634,0.002255171,0.00009546222,0.0006209621,0.004070717,0.001429727,0.0006907199,0.01051565,0.8889866,0.0001210093],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03487647,0.001317851,0.008937892,0.001992257,0.001251823,0.002973906,0.8634913,0.001942311,0.08321622],"genre_scores_gemma":[0.2401384,0.004605161,0.03709231,0.004045745,0.00087589,0.03720928,0.5645344,0.002111929,0.1093869],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2094553,"threshold_uncertainty_score":0.7006977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5663816369745452,"score_gpt":0.4609156418465546,"score_spread":0.1054659951279906,"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."}}