{"id":"W2043798185","doi":"10.1021/ed082p122","title":"Low-Cost Thermocouple Signal-Conditioning Module","year":2005,"lang":"en","type":"article","venue":"Journal of Chemical Education","topic":"Advanced Sensor Technologies Research","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Signal conditioning; Thermocouple; Conditioning; SIGNAL (programming language); Computer science; Electrical engineering; Materials science; Engineering; Thermodynamics; Mathematics; Physics; Power (physics); Statistics","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":[0.000489233,0.001025658,0.00116311,0.001220483,0.0004957108,0.0006208009,0.00243117,0.0009654582,0.03749857],"category_scores_gemma":[0.001342586,0.0005261059,0.0004450631,0.0008133616,0.0003077413,0.0009635556,0.0006843422,0.0009067532,0.01309239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004206063,"about_ca_system_score_gemma":0.0005073961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003255866,"about_ca_topic_score_gemma":0.0002237867,"domain_scores_codex":[0.9988151,0.00009272232,0.00007749656,0.0002870302,0.0006338875,0.0000937341],"domain_scores_gemma":[0.9991659,0.0002015892,0.00009986617,0.0001525767,0.0003234186,0.00005675272],"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":[0.0005764223,0.000581128,0.001483819,0.001361179,0.00006324553,0.0002613041,0.00009426344,0.0009564091,0.8307384,0.002768978,0.02135415,0.1397607],"study_design_scores_gemma":[0.0001988338,0.0009757407,0.005065126,0.00006453104,0.0001736616,0.002128969,0.00003532335,0.01659684,0.8503424,0.0005856064,0.1237364,0.00009657701],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1240292,0.002339844,0.8032534,0.0008141657,0.001402673,0.004441345,0.00323589,0.03071707,0.02976641],"genre_scores_gemma":[0.4935946,0.001750627,0.3977961,0.002588054,0.001133137,0.004385425,0.004753602,0.001322074,0.09267638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03749857,"threshold_uncertainty_score":0.1254452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009981932991114625,"score_gpt":0.2839454149865399,"score_spread":0.2739634819954253,"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."}}