{"id":"W1534274341","doi":"10.1109/eeeic.2015.7165254","title":"Pressure-based prediction of harvestable energy for powering environmental monitoring systems","year":2015,"lang":"en","type":"article","venue":"","topic":"Solar Radiation and Photovoltaics","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Reliability (semiconductor); Energy (signal processing); Computer science; Energy balance; Environmental science; Independence (probability theory); Real-time computing; Reliability engineering; Engineering; Power (physics)","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":[0.000267693,0.0004984511,0.000478695,0.000298454,0.0002578672,0.0004959459,0.0004580087,0.0003808799,0.0005811991],"category_scores_gemma":[0.001186333,0.0002010377,0.0002263806,0.0003522602,0.0001489115,0.0005192925,0.00025244,0.0005518821,0.0001668722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003140467,"about_ca_system_score_gemma":0.0003094333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004515238,"about_ca_topic_score_gemma":0.005387822,"domain_scores_codex":[0.9999287,0.00001405277,0.000005052902,0.00001612933,0.00002743697,0.000008700053],"domain_scores_gemma":[0.999698,0.0001937699,0.00003448793,0.00001459356,0.00004598502,0.00001313636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007257015,0.00004274486,0.003727623,0.00004900849,0.00001969207,0.00004501404,0.0000258464,0.9452349,0.005314872,0.0004983106,0.0004519628,0.04451751],"study_design_scores_gemma":[0.000001149518,0.000005488648,0.0004433526,7.018129e-7,0.000001141121,0.000001796064,0.000001388911,0.9988588,0.000551594,0.00009310607,0.00004029785,0.000001250543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.331219,0.0006298667,0.6632129,0.0002961129,0.00007249746,0.00006688583,0.000368177,0.001416675,0.002717895],"genre_scores_gemma":[0.97683,0.0002041534,0.02227591,0.00001215558,0.00003042314,0.00003856103,0.0001207639,0.00002108589,0.0004669719],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004515238,"threshold_uncertainty_score":0.00897789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03401315945848918,"score_gpt":0.2210896424955764,"score_spread":0.1870764830370873,"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."}}