{"id":"W2299960721","doi":"10.15200/winn.144703.34527","title":"Move over DNA: Here comes forensic pollen analysis","year":2015,"lang":"en","type":"dataset","venue":"The Winnower","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Forensic science; Pollen; Computational biology; Computer science; Biology; Genetics; Botany","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":[0.01524888,0.001159472,0.001181845,0.002929328,0.003628175,0.009998658,0.002570408,0.01000823,0.02448015],"category_scores_gemma":[0.0507214,0.001309459,0.001056227,0.001275845,0.006437289,0.01431924,0.006769514,0.02676124,0.01954656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001881269,"about_ca_system_score_gemma":0.004561223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003432177,"about_ca_topic_score_gemma":0.007691632,"domain_scores_codex":[0.9902372,0.002359387,0.0007508086,0.00114658,0.004978059,0.0005280108],"domain_scores_gemma":[0.9676009,0.01309558,0.001252971,0.003179368,0.009567662,0.005303433],"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":[0.00005796148,0.00006920627,0.0009836354,0.000336262,0.00002344955,0.000338152,0.0009204756,0.00005113941,0.0007661064,0.005759363,0.7069837,0.2837106],"study_design_scores_gemma":[0.0000141656,0.00005578812,0.0005665723,0.001223689,0.00001258178,0.0009248417,0.001041772,0.00007254912,0.0003501117,0.01415345,0.9815449,0.00003968319],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"dataset","genre_scores_codex":[0.001448557,0.1301458,0.01947303,0.7117563,0.1086109,0.0002556475,0.0004191433,0.001575611,0.02631503],"genre_scores_gemma":[0.01696602,0.2147375,0.09211458,0.5005571,0.08956452,0.0004861469,0.0009625929,0.001988275,0.08262328],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.02448015,"threshold_uncertainty_score":0.08189428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01490287073527509,"score_gpt":0.2995901337970567,"score_spread":0.2846872630617816,"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."}}