{"id":"W2891054079","doi":"10.31618/vadnd.v1i13.138","title":"EXPERIENCE OF ADVANCED COUNTRIES IN APPLICATION OF PRE-TRIAL SETTLEMENT IN CONSTRUCTION","year":2018,"lang":"en","type":"article","venue":"UKRAINIAN ASSEMBLY OF DOCTORS OF SCIENCES IN PUBLIC ADMINISTRATION","topic":"Land Use and Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tellabs (Canada)","funders":"","keywords":"Ukrainian; Settlement (finance); Context (archaeology); Legislation; State (computer science); Political science; Order (exchange); Decentralization; Politics; Public administration; Law and economics; Law; Business; Sociology; Computer science; Finance; Geography","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":[0.002095408,0.00007919686,0.000231242,0.0004132589,0.00006299897,0.00002333655,0.0003593225,0.00007359382,0.0000244661],"category_scores_gemma":[0.0003790364,0.00007554173,0.00002997528,0.001198316,0.001657236,0.0007207756,0.00003834656,0.00004423812,3.116025e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007304384,"about_ca_system_score_gemma":0.0005216441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001020496,"about_ca_topic_score_gemma":0.01198343,"domain_scores_codex":[0.9979658,0.0001199644,0.0008331331,0.0002389161,0.0006352135,0.0002069941],"domain_scores_gemma":[0.9988732,0.0001220685,0.000666191,0.0001314073,0.0001742959,0.00003284397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.002243424,0.001227077,0.3493116,0.0002107603,0.00001682129,8.596322e-7,0.1695793,0.0001101437,0.006678097,0.4280262,0.00002248701,0.04257326],"study_design_scores_gemma":[0.02759168,0.0102649,0.4954599,0.0009448065,0.00003816077,0.000001867425,0.2419145,0.002546792,0.1677163,0.01245656,0.03993022,0.001134244],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935527,0.00001540738,0.0001932497,0.0006164635,0.0002014214,0.0006250413,0.000009026565,0.000006225919,0.004780427],"genre_scores_gemma":[0.9982978,0.00005521753,0.001536489,0.00001232615,0.00004069187,0.00004135973,0.000004038063,0.000002088791,0.00001001507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4155697,"threshold_uncertainty_score":0.6687036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02520117777321148,"score_gpt":0.3617760575454981,"score_spread":0.3365748797722866,"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."}}