{"id":"W3196071263","doi":"10.1109/aim46487.2021.9517696","title":"Automatic Material Classification via Proprioceptive Sensing and Wavelet Analysis During Excavation","year":2021,"lang":"en","type":"article","venue":"","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"NCR","keywords":"Wavelet; Excavation; Computer science; Artificial intelligence; Pattern recognition (psychology); Geology; Geotechnical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004360338,0.000387439,0.0003931755,0.00161904,0.0002188526,0.0005562853,0.0004878459,0.0004148097,0.0004787308],"category_scores_gemma":[0.001398609,0.0002563508,0.0002766314,0.001092389,0.0003002085,0.0007305006,0.0004123653,0.0002640515,0.0003082499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001278948,"about_ca_system_score_gemma":0.0002357532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007682384,"about_ca_topic_score_gemma":0.001410553,"domain_scores_codex":[0.9996444,0.00005444402,0.00002161664,0.00008824438,0.0001506766,0.00004070003],"domain_scores_gemma":[0.9994093,0.0002180896,0.0001388058,0.00005813086,0.0001485797,0.00002709559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005720841,0.0001473977,0.01989021,0.0002351035,0.00005338743,0.000244655,0.000365388,0.02420231,0.2875993,0.0006234832,0.0007958668,0.6652708],"study_design_scores_gemma":[0.00004710957,0.0003672112,0.1182175,0.00005120479,0.00006101177,0.0005550517,0.0004897676,0.7760097,0.09991168,0.001795801,0.002420767,0.00007325952],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4980578,0.0002320191,0.4996601,0.000058176,0.00004001212,0.00005167214,0.0001289158,0.0005385896,0.001232762],"genre_scores_gemma":[0.8445969,0.0001866789,0.153986,0.00001910915,0.00002467475,0.00004014917,0.0002120845,0.00005423408,0.0008802759],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00161904,"threshold_uncertainty_score":0.002306044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01059052813941784,"score_gpt":0.2299262990328187,"score_spread":0.2193357708934008,"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."}}