{"id":"W3212073090","doi":"","title":"EKOLOGIK TA’LIM SOHASIDA O’SIMLIKLARNI TOMCHILATIB SUG’ORISH TEXNOLOGIYASI","year":2021,"lang":"ru","type":"article","venue":"Журнал естественных наук","topic":"Education, Innovation and Language Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Training (meteorology); Population; Desert (philosophy); Simple (philosophy); Natural resource; Business; Quarter (Canadian coin); Geography; Environmental protection; Political science; Ecology; Archaeology; Sociology; Biology; Demography; Meteorology","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001628705,0.0007432385,0.000972772,0.0003122583,0.002453436,0.0006280487,0.001002846,0.00079944,0.03943409],"category_scores_gemma":[0.004518324,0.0007591209,0.0004156592,0.003448467,0.00148432,0.0006375343,0.0005120841,0.001082951,0.0009012378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004325011,"about_ca_system_score_gemma":0.001659909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002524123,"about_ca_topic_score_gemma":0.01711494,"domain_scores_codex":[0.9932935,0.001145369,0.001278641,0.001429606,0.001204167,0.001648665],"domain_scores_gemma":[0.9954514,0.0007644735,0.0007416958,0.00115045,0.0014834,0.0004086172],"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":[0.00006158296,0.001768426,0.1805006,0.0002624931,0.0006723157,0.0003706957,0.1276279,0.00002714031,0.0009612065,0.136839,0.4771183,0.07379037],"study_design_scores_gemma":[0.0009857442,0.0001690641,0.1212472,0.0001684291,0.0002053508,0.00003297545,0.1500748,0.00002464429,0.001306517,0.004558449,0.7200313,0.001195537],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4558798,0.01796205,0.0003468212,0.08110381,0.0164349,0.001242925,0.0002357419,0.0009531587,0.4258408],"genre_scores_gemma":[0.9167737,0.005373255,0.001597341,0.005960706,0.004014847,0.00009100136,0.0002756376,0.00008693209,0.06582658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4608939,"threshold_uncertainty_score":0.9998767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04047707026123566,"score_gpt":0.3701862387932108,"score_spread":0.3297091685319752,"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."}}