{"id":"W2073864557","doi":"10.1063/1.4818066","title":"Low background counting techniques at SNOLAB","year":2013,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Snolab","funders":"","keywords":"Icon; Citation; Computer science; Information retrieval; Download; World Wide Web; Filter (signal processing); Programming language","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":[0.001833615,0.001201865,0.000735008,0.006094211,0.00189798,0.003015517,0.002479284,0.001441899,0.1053363],"category_scores_gemma":[0.003045522,0.001150868,0.0005232066,0.003233406,0.0007582259,0.003246862,0.002465735,0.00320637,0.05634293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001487555,"about_ca_system_score_gemma":0.0009419436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001069176,"about_ca_topic_score_gemma":0.002751186,"domain_scores_codex":[0.9977154,0.0003138116,0.00006823189,0.0002753422,0.00146594,0.0001612852],"domain_scores_gemma":[0.9981298,0.0003671684,0.0001126609,0.0004731418,0.0007490985,0.0001680633],"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":[0.0006293292,0.0001989161,0.001864641,0.0005486213,0.00009710689,0.0007378379,0.0004215345,0.001174433,0.1467248,0.08917526,0.3580513,0.4003763],"study_design_scores_gemma":[0.00007109358,0.0001029321,0.001633323,0.0002602333,0.00005717244,0.001081303,0.0001796707,0.01946456,0.2711046,0.02463053,0.6812499,0.0001646799],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01639045,0.005545529,0.5705802,0.004952136,0.002682137,0.0003561908,0.004044923,0.03799481,0.3574535],"genre_scores_gemma":[0.188955,0.004345438,0.5403479,0.002651059,0.0008437285,0.0008591388,0.006753079,0.01849333,0.2367513],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1053363,"threshold_uncertainty_score":0.352385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01554771504025188,"score_gpt":0.2228228769228571,"score_spread":0.2072751618826053,"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."}}