{"id":"W2329753344","doi":"10.4133/sageep.28-075","title":"CHARACTERIZATION OF AN SIP SAMPLE HOLDER: LESSONS FROM EXPERIMENT","year":2015,"lang":"en","type":"article","venue":"Symposium on the Application of Geophysics to Engineering and Environmental Problems 2015","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Characterization (materials science); Sample (material); Computer science; Materials science; Nanotechnology; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007206461,0.0001298053,0.0001375161,0.00004108425,0.00001968048,0.000009060738,0.0001213821,0.00004046848,0.000001996474],"category_scores_gemma":[0.000001771284,0.0001073929,0.0000280419,0.0001170151,0.00002636609,0.00007050388,0.00002740784,0.00006627981,0.000007769288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002402808,"about_ca_system_score_gemma":0.000002756787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000671189,"about_ca_topic_score_gemma":6.48166e-7,"domain_scores_codex":[0.9993889,0.000008877633,0.0001731964,0.0001504283,0.0001587738,0.0001198183],"domain_scores_gemma":[0.9995747,0.000029029,0.00004396773,0.0002438467,0.000007198096,0.0001012296],"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":[0.000007370774,0.00007448053,0.0000525023,0.00001461128,0.00001783053,2.73571e-8,0.0003427545,0.04014762,0.9565039,0.0004919519,0.00001113841,0.002335817],"study_design_scores_gemma":[0.0003077684,0.0003350632,0.003929885,0.00003240007,0.00002304947,5.017624e-7,0.00007930439,0.12368,0.868055,0.0009673127,0.002305115,0.0002845431],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9788009,0.00006881233,0.02037235,0.0001931965,0.00003752751,0.000290051,0.0001315763,0.00005905504,0.00004652955],"genre_scores_gemma":[0.9990296,0.00006124258,0.0005562748,0.00002114267,0.00004547071,0.00009983572,0.0001574451,0.00002271546,0.000006220872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08844887,"threshold_uncertainty_score":0.4379356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009317707554184842,"score_gpt":0.1972993397473204,"score_spread":0.1879816321931355,"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."}}