{"id":"W2766832172","doi":"10.7287/peerj.preprints.3307v1","title":"Cannabis chemovar classification: terpenes hyper-classes and targeted genetic markers for accurate discrimination of flavours and effects","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Cannabis and Cannabinoid Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Terpene; Classification scheme; Class (philosophy); Machine learning; Benchmark (surveying); Cluster analysis; Artificial intelligence; Computer science; Biology; Geography; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001374669,0.0005587547,0.0005966878,0.001428979,0.0007117498,0.001996797,0.000888559,0.0007789907,0.002924722],"category_scores_gemma":[0.00292043,0.0001884211,0.0006466866,0.001263563,0.0007356896,0.00116239,0.001155261,0.001450684,0.001111966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008545886,"about_ca_system_score_gemma":0.0009564452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002962282,"about_ca_topic_score_gemma":0.003918058,"domain_scores_codex":[0.999243,0.000207087,0.00004120489,0.0002833826,0.0001484593,0.00007694843],"domain_scores_gemma":[0.9984124,0.0005162057,0.0002373051,0.0004355947,0.000251538,0.0001470376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001911978,0.0006592247,0.1143577,0.0004378466,0.0002897803,0.0002811673,0.0006918935,0.03171148,0.2504154,0.03401747,0.003722171,0.561504],"study_design_scores_gemma":[0.0001399225,0.0006820082,0.1527407,0.0001921063,0.0003000484,0.0005913496,0.000686975,0.6154467,0.1281538,0.07265893,0.02816255,0.0002448319],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5910566,0.001379629,0.3928437,0.001036729,0.0002379295,0.0003323734,0.002172573,0.001238216,0.009702333],"genre_scores_gemma":[0.8107279,0.0004187727,0.1818574,0.0002034579,0.00007160408,0.0001206336,0.002205478,0.0001218876,0.004272865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002962282,"threshold_uncertainty_score":0.009784102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03179373674929271,"score_gpt":0.334066489510727,"score_spread":0.3022727527614343,"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."}}