{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.002033364,0.0003114742,0.0004208331,0.0005673429,0.0002564019,0.002079276,0.009352852,0.0001708988,0.2592165],"category_scores_gemma":[0.08748291,0.0002486547,0.00006942105,0.001318799,0.00002546799,0.0003508412,0.01032854,0.0004231833,0.5365777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005935301,"about_ca_system_score_gemma":0.0002677865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001846453,"about_ca_topic_score_gemma":0.0006391505,"domain_scores_codex":[0.9936782,0.0001969447,0.0007826377,0.001964641,0.00291618,0.0004614654],"domain_scores_gemma":[0.9872872,0.004023108,0.0005841092,0.007440192,0.0004677183,0.0001976217],"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":[0.000002731192,0.00002082409,1.441986e-7,0.00003865268,0.00002315608,0.0001263973,0.00001644822,0.00001453116,1.232589e-8,0.00000211259,0.9902838,0.009471123],"study_design_scores_gemma":[0.00007791767,0.00001977789,0.00008699684,0.0004117851,0.00002271671,0.000002619513,0.0001903647,0.001678406,1.700749e-7,0.0003775875,0.9968397,0.0002919769],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[5.758353e-8,0.00004183202,0.00007910169,0.00005151095,0.002432869,0.0002460298,0.9968489,0.0001183596,0.0001813857],"genre_scores_gemma":[2.495023e-7,0.000004598714,0.0004091897,0.0001824954,0.0004388542,0.00003084365,0.9925935,0.00002052301,0.006319738],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2773612,"threshold_uncertainty_score":0.9999965,"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."}}