{"id":"W2900729012","doi":"10.5539/mas.v12n12p119","title":"Characterization by TGA, SEM, and EDX of Polymeric Matrices Used as Cocaine Camouflages","year":2018,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Forensic Toxicology and Drug Analysis","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Extraction (chemistry); Adsorption; Matrix (chemical analysis); Polymer; Thermogravimetric analysis; Gravimetric analysis; Materials science; Morphology (biology); Chromatography; Chemical engineering; Chemistry; Organic chemistry; Composite material; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0002381645,0.0003875055,0.0001406483,0.0008280476,0.0002534819,0.0002564176,0.0001203248,0.0003105661,0.0008581823],"category_scores_gemma":[0.0003562265,0.0001524873,0.0001943523,0.0004518259,0.0002349671,0.0002915618,0.0001247461,0.0003139778,0.0002201609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001169481,"about_ca_system_score_gemma":0.0001199303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005112657,"about_ca_topic_score_gemma":0.001858073,"domain_scores_codex":[0.9998196,0.0000198807,0.00001316781,0.00003108825,0.00009413363,0.00002225255],"domain_scores_gemma":[0.9997011,0.00009116019,0.00007761569,0.00002138586,0.00009365686,0.00001504389],"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":[0.00003060685,0.00001026937,0.0005668252,0.00006637739,0.000006477638,0.00009927596,0.00006210096,0.00009784444,0.996137,0.0000409169,0.00001264187,0.002869591],"study_design_scores_gemma":[0.000001656491,0.0001527046,0.01014803,0.00001420458,0.00002293902,0.000278562,0.0001260093,0.0005464601,0.9871396,0.00003296597,0.001529483,0.000007303655],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9840003,0.002104407,0.01063149,0.00003696023,0.00003621467,0.00005408283,0.0004511566,0.00004429867,0.002641033],"genre_scores_gemma":[0.973943,0.002154712,0.02064257,0.00004581093,0.00001117237,0.00008345937,0.0003812031,0.00005060204,0.002687492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008581823,"threshold_uncertainty_score":0.002870917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03136573147428557,"score_gpt":0.3691965194030942,"score_spread":0.3378307879288087,"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."}}