{"id":"W1874023101","doi":"10.13034/jsst.v8i1.44","title":"Thermoelectric Energy Harvesting Snow Pants: Turning Body Heat Into Usable Energy","year":2015,"lang":"en","type":"article","venue":"Journal of Student Science and Technology","topic":"Innovative Energy Harvesting Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Snow; Thermoelectric effect; Electrical engineering; Voltage; Thermoelectric cooling; Energy (signal processing); Energy harvesting; Mechanical engineering; Power (physics); Materials science; Thermoelectric generator; Physics; Thermodynamics; Engineering; Meteorology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001140693,0.0001977224,0.0003274925,0.001716632,0.000216835,0.0001232987,0.000986883,0.0001631432,0.000002058905],"category_scores_gemma":[0.001151631,0.0001608098,0.00002451973,0.003594008,0.0007512476,0.0006683643,0.0003276167,0.0004012854,0.000001313091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003131991,"about_ca_system_score_gemma":0.0002036671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004966138,"about_ca_topic_score_gemma":0.00001064291,"domain_scores_codex":[0.9981772,0.0000186064,0.0004706715,0.0002216788,0.0006192746,0.0004925771],"domain_scores_gemma":[0.9985921,0.00006961296,0.0001697707,0.0002338595,0.0008325304,0.0001021063],"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":[0.00001357909,0.0001193987,0.04719873,0.00001972747,0.0001347934,0.0002386896,0.0004921265,0.005225346,0.6186556,0.1123919,0.001469664,0.2140404],"study_design_scores_gemma":[0.00195388,0.002040062,0.01071948,0.0004985904,0.00006982169,0.001938269,0.00499641,0.03412947,0.8598706,0.05626661,0.0263926,0.00112423],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829236,0.002092024,0.01146711,0.000643745,0.0004726839,0.00002793849,2.419035e-7,0.0004384586,0.001934173],"genre_scores_gemma":[0.9949524,0.0002874085,0.004518632,0.00006258287,0.00007432883,0.000005812958,1.853403e-7,0.00001943303,0.00007915053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2412149,"threshold_uncertainty_score":0.6557633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589115018051917,"score_gpt":0.2548569385661812,"score_spread":0.2389657883856621,"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."}}