{"id":"W7030394965","doi":"","title":"Methodological specifics of forecasting the development of the industrial sector of a region’s economy factoring in the impact of shock “impulses” on it (Through the example of the republic of Tatarstan)","year":2015,"lang":"en","type":"other","venue":"zvestiya of the National Academy of Sciences of Belarus (National Academy of Sciences of Belarus)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Factoring; Investment (military); Shock (circulatory); Legislature; Foreign direct investment; Relation (database); Relevance (law); Economic integration; Russian federation; Globalization; Industrial relations","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","sts","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.0318202,0.0008126753,0.002259381,0.001437152,0.0004921482,0.00002900997,0.01230134,0.001000122,0.0001678208],"category_scores_gemma":[0.01200201,0.0003739938,0.001139473,0.007121467,0.02156729,0.0009216537,0.001693194,0.001777271,9.620142e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004673349,"about_ca_system_score_gemma":0.003929732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001689229,"about_ca_topic_score_gemma":0.00007012022,"domain_scores_codex":[0.9797151,0.002236308,0.005517801,0.001123866,0.01063826,0.000768678],"domain_scores_gemma":[0.9679634,0.01058817,0.01916825,0.0004526178,0.00170999,0.0001175847],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002811076,0.005972792,0.06423075,0.002920934,0.004181145,5.06328e-7,0.0393854,0.2800277,0.1176856,0.4368394,0.03906811,0.006876487],"study_design_scores_gemma":[0.006279131,0.002799808,0.334485,0.01128028,0.0008320683,0.0001437722,0.01247552,0.005429702,0.4178004,0.1944515,0.0120983,0.001924524],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9489779,0.001850102,0.00007786869,0.006645938,0.0003535377,0.004562892,0.004279763,0.00002172342,0.03323028],"genre_scores_gemma":[0.9937516,0.00008296643,0.005315971,0.000107557,0.0002093024,0.00003980176,0.000008918372,0.00007208334,0.0004118024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3001147,"threshold_uncertainty_score":0.9998712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6022482524577956,"score_gpt":0.4268281245037716,"score_spread":0.175420127954024,"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."}}