{"id":"W7061268915","doi":"","title":"Portable analytical platforms for disease diagnostics and environmental monitoring","year":2018,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Gyrotron and Vacuum Electronics Research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; McGill University","keywords":"Environmental monitoring; Disease monitoring; Condition monitoring; Environmental data","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0005794477,0.0008269638,0.0005516039,0.0009579294,0.0003836563,0.0009035612,0.0009152291,0.0007528996,0.01336095],"category_scores_gemma":[0.0006835226,0.0003923381,0.0004495892,0.0008206595,0.0002584239,0.0008230382,0.001124287,0.0007543194,0.007384599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002447769,"about_ca_system_score_gemma":0.0003851547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004823311,"about_ca_topic_score_gemma":0.0009491665,"domain_scores_codex":[0.999416,0.0000526749,0.00001801359,0.0001932417,0.0002512066,0.00006887894],"domain_scores_gemma":[0.9997072,0.00006447986,0.0000422745,0.0000351336,0.0001103962,0.00004048885],"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":[0.0003182293,0.0001793066,0.001786058,0.000559689,0.00006636976,0.0002073097,0.000117116,0.0004307979,0.8115456,0.001575717,0.01936269,0.1638512],"study_design_scores_gemma":[0.0001212771,0.001221361,0.01104052,0.0001216223,0.0002322299,0.0007401848,0.0003259784,0.006325138,0.740503,0.002478332,0.2367947,0.00009567442],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2810507,0.04568042,0.4935907,0.005181934,0.005575359,0.002525468,0.01667261,0.0139299,0.1357929],"genre_scores_gemma":[0.4743276,0.02221222,0.2730165,0.003047488,0.001752293,0.001891227,0.008821767,0.0006406732,0.2142903],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01336095,"threshold_uncertainty_score":0.04469681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01858318866219536,"score_gpt":0.281772402125317,"score_spread":0.2631892134631216,"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."}}