{"id":"W4221133708","doi":"10.1016/j.forsciint.2022.111287","title":"Concentrating forensic DNA sample extracts on the Microlab® STARlet using the Microlab® monitored multi-flow, positive pressure, evaporative extraction module unit","year":2022,"lang":"en","type":"article","venue":"Forensic Science International","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of the Environment, Conservation and Parks","funders":"","keywords":"Sample (material); Forensic science; Chromatography; Chemistry; Medicine; Veterinary medicine","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":[0.0006320668,0.0001730353,0.00009596602,0.00006446399,0.001203167,0.0001077646,0.0007623768,0.0000617859,0.00005692446],"category_scores_gemma":[0.0002354476,0.0001228109,0.00008686091,0.0002689639,0.0007149039,0.00002216651,0.0003416742,0.0002866037,0.00000217031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008592749,"about_ca_system_score_gemma":0.0001958398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001738654,"about_ca_topic_score_gemma":0.00003924797,"domain_scores_codex":[0.9984028,0.00013991,0.0002353919,0.0005081119,0.0004166228,0.0002971335],"domain_scores_gemma":[0.9988445,0.00009715495,0.000249913,0.0004033267,0.0003529224,0.00005216415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008700328,0.0000905518,0.001032053,8.777614e-7,0.00006176134,0.000002185475,0.0001916085,0.003808691,0.9898025,0.00213775,0.0008492097,0.001935826],"study_design_scores_gemma":[0.0004055008,0.0002943808,0.004708831,0.0000145109,0.00003368906,0.00008406102,0.001097111,0.06705563,0.9095314,0.0007879506,0.01572572,0.000261254],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9583117,0.0001004425,0.03819579,0.001392729,0.0004943918,0.0006333975,0.0005659689,0.00002175888,0.0002838099],"genre_scores_gemma":[0.9850227,0.00001021899,0.0130749,0.001062363,0.0001826308,0.0001424774,0.0003375881,0.00001598611,0.0001511802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08027112,"threshold_uncertainty_score":0.9253912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03217019659471178,"score_gpt":0.3256351176094355,"score_spread":0.2934649210147237,"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."}}