{"id":"W4298376281","doi":"10.33061/jeku.v22i1.7621","title":"OPTIMALISASI KETERBATASAN SUMBER DAYA MANUSIA DALAM PROGRAM PENDAFTARAN TANAH SISTEMATIS LENGKAP (PTSL) PADA KANTOR PERTANAHAN KABUPATEN KEBUMEN","year":2022,"lang":"id","type":"article","venue":"JURNAL EKONOMI DAN KEWIRAUSAHAAN","topic":"Coastal Management and Development","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Political science; Humanities; Physics; Art","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":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.00185439,0.001429153,0.001318765,0.0004067199,0.002375536,0.001127168,0.002562337,0.0002200165,0.004943557],"category_scores_gemma":[0.00005911895,0.001509215,0.0007023323,0.001042049,0.0005669197,0.001221817,0.005295887,0.001341988,0.0006754258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003014884,"about_ca_system_score_gemma":0.0002569619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001734296,"about_ca_topic_score_gemma":0.002116557,"domain_scores_codex":[0.9901546,0.0009499888,0.002066043,0.002280774,0.002258643,0.002290013],"domain_scores_gemma":[0.9959875,0.0001934148,0.001045079,0.001666402,0.00004904591,0.001058594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001426974,0.004476638,0.7004976,0.0009350771,0.00157797,0.001919639,0.005724553,0.001842543,0.003822911,0.0004890172,0.03008181,0.2472053],"study_design_scores_gemma":[0.002138701,0.001329981,0.630818,0.0002069459,0.0004063007,0.0001736853,0.003319598,0.002197739,0.0003052872,0.00001813293,0.3571767,0.001908943],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9457494,0.0006551514,0.00003881537,0.001590906,0.001973158,0.003593409,0.0003338954,0.0003437898,0.04572146],"genre_scores_gemma":[0.9804376,0.0002946984,0.0007064181,0.0005285595,0.0003159862,0.0009155211,0.000634776,0.0002308228,0.01593562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3270949,"threshold_uncertainty_score":0.9999098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01707780587932944,"score_gpt":0.2349116826636232,"score_spread":0.2178338767842938,"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."}}