{"id":"W2549823869","doi":"","title":"ENV-638: ADVANCED TECHNIQUES FOR SITE CHARACTERIZATION: REAL-TIME HIGH-RESOLUTION SITE CHARACTERIZATION OF THE SUBSURFACE USING MIP, LIF AND HPT","year":2016,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Engineering Applied Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Characterization (materials science); Remote sensing; Mineralogy; Geology; Environmental science; Chemistry; Materials science; Nanotechnology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001245824,0.0008596649,0.0005249412,0.001413521,0.0004005186,0.0009159885,0.001053064,0.001100671,0.004587854],"category_scores_gemma":[0.0008069474,0.0005251804,0.0004883408,0.001043299,0.0005680277,0.001566067,0.0008333169,0.001157105,0.002315568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007344,"about_ca_system_score_gemma":0.000739512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002668345,"about_ca_topic_score_gemma":0.003541339,"domain_scores_codex":[0.9990568,0.00007558122,0.00003422924,0.0001792176,0.0005822049,0.00007211653],"domain_scores_gemma":[0.9995289,0.00008555033,0.00008137355,0.00007658714,0.0002025584,0.00002505682],"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":[0.00008341639,0.00004555571,0.001106488,0.000217117,0.00001721265,0.00009159305,0.00009993113,0.0007927365,0.9288811,0.0009905853,0.003185774,0.06448864],"study_design_scores_gemma":[0.00003253362,0.0001416234,0.005827358,0.0000511999,0.00002862137,0.000625105,0.0001284214,0.02736079,0.9149952,0.001282509,0.04943357,0.00009317683],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07610826,0.00257304,0.8873387,0.0005387966,0.0001461129,0.0003751039,0.004320938,0.01490705,0.01369194],"genre_scores_gemma":[0.1554263,0.002295318,0.8183519,0.0004431653,0.00005765934,0.001059376,0.004550596,0.00124516,0.01657062],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004587854,"threshold_uncertainty_score":0.0153479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03256943458356244,"score_gpt":0.2642668312835583,"score_spread":0.2316973966999959,"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."}}