{"id":"W4409423074","doi":"10.1016/j.buildenv.2025.112963","title":"Graph-based spatial–temporal prediction and feature interaction analysis of CO<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si54.svg\" display=\"inline\" id=\"d1e2369\"><mml:msub><mml:mrow/><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:math> and occupant in large indoor space","year":2025,"lang":"lv","type":"article","venue":"Building and Environment","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Graph; Scalable Vector Graphics; Computer science; Theoretical computer science; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008700709,0.0003556212,0.0002377997,0.0003608398,0.0004653848,0.0002410561,0.000254446,0.000639213,0.009097803],"category_scores_gemma":[0.0001701319,0.0005362838,0.0003264512,0.0004856887,0.0005854351,0.0005178179,0.0004298351,0.0005334931,0.00005384716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003510846,"about_ca_system_score_gemma":0.0001121753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002245513,"about_ca_topic_score_gemma":0.001539143,"domain_scores_codex":[0.9968697,0.0001777969,0.0006796169,0.0008822024,0.0007417886,0.0006488562],"domain_scores_gemma":[0.998155,0.0003599505,0.0005875265,0.0005782899,0.000009313449,0.0003099312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007594797,0.003551706,0.1624371,0.005539051,0.007949888,0.001113998,0.01560186,0.06467531,0.1058052,0.426799,0.1511205,0.04781167],"study_design_scores_gemma":[0.00148617,0.000652944,0.05760053,0.0007758631,0.001649091,0.00007256198,0.001072205,0.5197026,0.4136913,0.00001968211,0.002697832,0.000579164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899784,0.0009599225,0.002169384,0.0005528081,0.0004177627,0.00005929494,0.00039711,0.00003786508,0.005427478],"genre_scores_gemma":[0.9957053,0.001676736,0.00108716,0.0003198372,0.0001519447,0.0001720086,0.0007197416,0.00007670258,0.00009058955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4550273,"threshold_uncertainty_score":0.9997089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01035546067618219,"score_gpt":0.2315209400526183,"score_spread":0.2211654793764361,"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."}}