{"id":"W2623223676","doi":"10.1021/acssensors.7b00112","title":"An Inexpensive, Single Use Carbon-Based Sensor for the Rapid and Early Detection of Hydrocarbon Leaks","year":2017,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canada Excellence Research Chairs, Government of Canada; Alberta Innovates; Alberta Innovates - Technology Futures; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Paraffin wax; Hexane; Wax; Materials science; Hydrocarbon; Carbon fibers; Chemical engineering; Solvent; Nanoparticle; Evaporation; Fabrication; Carbon nanotube; Electrical resistivity and conductivity; Nanotechnology; Organic chemistry; Chemistry; Composite material","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003541726,0.0008275794,0.000555261,0.0008070233,0.0003389893,0.0004032035,0.001141448,0.001265634,0.001041844],"category_scores_gemma":[0.0005255177,0.0003290818,0.0002583471,0.0004601396,0.0003492388,0.0008887033,0.0004104942,0.0008188405,0.0005996973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005474746,"about_ca_system_score_gemma":0.0005953767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007053155,"about_ca_topic_score_gemma":0.002422429,"domain_scores_codex":[0.9991634,0.00006157286,0.00002913615,0.0001403191,0.00054824,0.00005733172],"domain_scores_gemma":[0.9996586,0.00006884214,0.00006620647,0.00002214296,0.0001196076,0.00006448939],"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":[0.0000332936,0.00002894314,0.0001180621,0.0001078451,0.000004709889,0.00006035785,0.000007013191,0.00006555102,0.9919635,0.00008405383,0.0002641278,0.007262437],"study_design_scores_gemma":[0.000009446476,0.0001906724,0.0007833933,0.000007148386,0.00001431012,0.0003080488,0.000008758911,0.003027858,0.9927947,0.00002879193,0.002799426,0.00002744273],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6396742,0.01979125,0.3227611,0.001939145,0.001135382,0.001040414,0.002292646,0.003633928,0.007731964],"genre_scores_gemma":[0.6447392,0.004457837,0.3386556,0.0005579174,0.0001532479,0.0002900113,0.0008343778,0.0001004625,0.01021142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001265634,"threshold_uncertainty_score":0.003972173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02723519866502373,"score_gpt":0.2430513426210637,"score_spread":0.21581614395604,"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."}}