{"id":"W4409290321","doi":"10.3390/en18081913","title":"A Review and Characterization of Energy-Harvesting Resources in Buildings with a Case Study of a Commercial Building in a Cold Climate—Toronto, Canada","year":2025,"lang":"en","type":"review","venue":"Energies","topic":"Innovative Energy Harvesting Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Architectural engineering; Cold climate; Characterization (materials science); Climate change; Environmental science; Civil engineering; Environmental planning; Engineering; Geography; Meteorology; Geology; Materials science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0007076889,0.0008702509,0.001060054,0.005759542,0.0004880027,0.001324621,0.0009050136,0.0005862215,0.002291366],"category_scores_gemma":[0.0008141311,0.0003313643,0.0006958641,0.009332628,0.0005543103,0.0008179312,0.0004216045,0.0004313134,0.0004103422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003890829,"about_ca_system_score_gemma":0.007857249,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1601637,"about_ca_topic_score_gemma":0.2906952,"domain_scores_codex":[0.9995863,0.00004318171,0.00006916064,0.00005233878,0.0002093879,0.00003970509],"domain_scores_gemma":[0.9992986,0.0002564723,0.00009860638,0.00001780205,0.0002970578,0.00003136304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007539385,0.00006371963,0.001326607,0.1079372,0.0002567911,0.0005207799,0.0006114775,0.00249941,0.004313645,0.007129958,0.0212804,0.8539847],"study_design_scores_gemma":[0.000003851356,0.00009230332,0.007764415,0.01713973,0.0004242901,0.0007178639,0.0004374586,0.0002953354,0.001591694,0.0005768881,0.9709131,0.00004309],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0008479379,0.9962394,0.0002027297,0.00009731288,0.00005500586,0.00000953194,0.0001132909,0.000004394616,0.002430412],"genre_scores_gemma":[0.00449903,0.9943342,0.0002933705,0.00004976829,0.00002648427,0.00000521039,0.0001023909,0.000001900979,0.0006876416],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8398362,"threshold_uncertainty_score":0.318463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01445871898446345,"score_gpt":0.2585089374908432,"score_spread":0.2440502185063797,"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."}}