{"id":"W6957884063","doi":"10.6068/dp16142fac9db22","title":"TREND: United Nations Economic Commission for Europe. Gender Statistics [Archive]: Convictions by Type | Country: Croatia | Selection 1: Drug crime | Selection 2: Male, 1980 - 2006. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 054-003-056","year":2018,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Commission; Official statistics; Crime statistics; Criminal justice; International Standard Industrial Classification; Selection (genetic algorithm); Economic data","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00194639,0.001831778,0.001930809,0.006913336,0.0008964195,0.003036599,0.002692471,0.001007532,0.07221341],"category_scores_gemma":[0.01225987,0.001138657,0.001157507,0.02181756,0.000345362,0.003152872,0.001677709,0.003150045,0.08505993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002276964,"about_ca_system_score_gemma":0.006343428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1117822,"about_ca_topic_score_gemma":0.07069618,"domain_scores_codex":[0.9976248,0.0002890747,0.0003605139,0.0005073698,0.0008510279,0.0003672594],"domain_scores_gemma":[0.9903879,0.001022365,0.001236818,0.0008346047,0.00607469,0.0004435669],"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":[0.00002427046,0.00001339536,0.000877356,0.0002275291,0.00001249912,0.000006657818,0.00001146532,0.00006927014,0.00001050521,0.0003129361,0.9962923,0.00214172],"study_design_scores_gemma":[0.00009670041,0.00001797804,0.01679162,0.0007423387,0.00003111872,0.00002865757,0.0001989511,0.0001730362,0.0001119035,0.0006113563,0.9811689,0.00002744018],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000112006,0.00007631825,0.00004961839,0.00008641066,0.00008592679,0.00002400631,0.9982773,0.00006462904,0.001223775],"genre_scores_gemma":[0.0004484301,0.0001564176,0.0002279691,0.00006144523,0.00002709317,0.0001441487,0.997001,0.00007489071,0.001858625],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1117822,"threshold_uncertainty_score":0.2415779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0290999280780406,"score_gpt":0.293603889228837,"score_spread":0.2645039611507964,"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."}}