{"id":"W2047185702","doi":"","title":"Indeks giełdowy jako wskaźnik wyprzedzający koniunkturę","year":2012,"lang":"pl","type":"article","venue":"RepoS (Uniwersytetu Przyrodniczo-Humanistycznego w Siedlcach)","topic":"Polish socio-economic development","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Index (typography); Quarter (Canadian coin); Prosperity; Stock market index; Gross domestic product; Economics; Economic indicator; Econometrics; Stock market; Geography; Macroeconomics; Economic growth; Computer science","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":["metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.005367493,0.002630127,0.003998978,0.001978392,0.001954769,0.00158599,0.00327687,0.002289275,0.009693771],"category_scores_gemma":[0.00111233,0.003547141,0.001795794,0.001580675,0.001148916,0.003691693,0.001994695,0.0029828,0.02401613],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005562838,"about_ca_system_score_gemma":0.0008531042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001841472,"about_ca_topic_score_gemma":0.0002049266,"domain_scores_codex":[0.9836068,0.0004439291,0.005821604,0.003656409,0.0006844532,0.005786832],"domain_scores_gemma":[0.9870985,0.000679725,0.004627767,0.004789039,0.0003577527,0.00244725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005052105,0.00500054,0.2422383,0.001257419,0.004968888,0.0003534571,0.03659398,0.0001654359,0.0004485105,0.6106612,0.08919707,0.008609953],"study_design_scores_gemma":[0.00451039,0.0003870037,0.06230285,0.000318881,0.0003893161,0.0005153443,0.002875556,0.0004767178,0.0007207752,0.006920742,0.9151737,0.005408705],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.465088,0.02630267,0.0007754089,0.002513189,0.01680466,0.002220144,0.001015564,0.0008624584,0.4844179],"genre_scores_gemma":[0.8913195,0.002660631,0.002073666,0.002307241,0.003523548,0.000280173,0.0005351903,0.0007350229,0.09656509],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8259767,"threshold_uncertainty_score":0.9994504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04788088827247991,"score_gpt":0.230071212761347,"score_spread":0.1821903244888671,"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."}}