{"id":"W3006349826","doi":"","title":"Handheld Near Infrared spectroscopy for cannabis analysis: from the analytical problem to the chemometric solution","year":2020,"lang":"fr","type":"article","venue":"ORBi (University of Liège)","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mobile device; Spectroscopy; Near-infrared spectroscopy; Infrared; Analytical Chemistry (journal); Computer science; Chemistry; Chromatography; Physics; Optics; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000280855,0.0003235561,0.0007510682,0.0002412566,0.0007437074,0.0001328321,0.001249755,0.0003068916,0.004419568],"category_scores_gemma":[0.0001684037,0.0002842831,0.0008080516,0.008748514,0.0004372891,0.0002020041,0.0003409222,0.0004796333,0.0001475361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000313486,"about_ca_system_score_gemma":0.0002773361,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01191405,"about_ca_topic_score_gemma":0.001008267,"domain_scores_codex":[0.9978213,0.00007694302,0.000325763,0.0006717278,0.0005035204,0.0006006974],"domain_scores_gemma":[0.9979322,0.0004072151,0.0003286525,0.0006875669,0.0002781577,0.0003662196],"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":[0.001626348,0.0007524825,0.0674279,0.0005643557,0.01792542,0.00004685409,0.01693205,0.002238536,0.01845828,0.002195695,0.8696091,0.00222294],"study_design_scores_gemma":[0.005162133,0.001348997,0.04012113,0.0001934834,0.06492957,0.000006938826,0.03191412,0.171934,0.08309779,0.00142734,0.5977852,0.002079302],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2704128,0.008862628,0.2037142,0.5046899,0.0002380383,0.001021811,0.002082614,0.0001464048,0.00883167],"genre_scores_gemma":[0.9469993,0.0003993657,0.01518925,0.001754632,0.0007116878,0.000003883692,0.0002025954,0.00003875573,0.03470053],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6765865,"threshold_uncertainty_score":0.999961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02332699167780036,"score_gpt":0.2445119002520997,"score_spread":0.2211849085742993,"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."}}