{"id":"W3153105230","doi":"10.21203/rs.3.rs-364242/v1","title":"A method of value measurement based on conditional probability theory in economics","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Decision-Making Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Community College","funders":"","keywords":"Value (mathematics); Random variable; Variance (accounting); Measure (data warehouse); Conditional expectation; Econometrics; Expected value; Conditional probability distribution; Conditional probability; Variable (mathematics); Statistics; Probability distribution; Mathematics; Perspective (graphical); Conditional variance; Probability theory; Computer science; Economics; Data mining; Artificial intelligence; Autoregressive conditional heteroskedasticity","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01989862,0.0002312332,0.0004911083,0.0007712154,0.00007820215,0.000151462,0.001935677,0.0002748675,0.00003800652],"category_scores_gemma":[0.004394062,0.000227527,0.0002117024,0.0005349905,0.0001630304,0.000164246,0.0025782,0.001453008,0.000004239278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001609698,"about_ca_system_score_gemma":0.002444332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004466473,"about_ca_topic_score_gemma":0.00003358488,"domain_scores_codex":[0.9921057,0.003637874,0.0006214677,0.001226711,0.001962422,0.0004458835],"domain_scores_gemma":[0.9922413,0.003483161,0.0002056766,0.002360663,0.001599023,0.0001101986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001747718,0.001096817,0.0003971057,0.0007521211,0.00003912121,0.0000704889,0.0004087721,0.2528402,0.0002837269,0.617586,0.0001361936,0.1262147],"study_design_scores_gemma":[0.0001944323,0.0001528461,0.002758313,0.001169607,0.000001633806,0.000001703394,0.00002607473,0.1599927,0.006582151,0.8287731,0.0001737318,0.000173743],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002972696,0.0001109012,0.993718,0.0005621154,0.00008196766,0.001237907,0.00004943441,0.0001016707,0.001165261],"genre_scores_gemma":[0.4244089,0.00002221014,0.5751393,0.00004800912,0.00002192598,0.0003208791,0.00001890865,0.00001453929,0.000005265708],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4214362,"threshold_uncertainty_score":0.9278283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1570270707877233,"score_gpt":0.4505545488511848,"score_spread":0.2935274780634615,"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."}}