{"id":"W4390468218","doi":"10.3390/buildings14010102","title":"Evaluating Indoor Air Quality Monitoring Devices for Healthy Homes","year":2023,"lang":"en","type":"article","venue":"Buildings","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Indoor air quality; Usability; Computer science; Air quality index; Quality (philosophy); Ventilation (architecture); Environmental science; Engineering; Human–computer interaction; Environmental engineering; Geography","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":[0.005181846,0.0009326506,0.0005068241,0.0006365803,0.000280378,0.001103886,0.0008999132,0.000927967,0.002152102],"category_scores_gemma":[0.01563777,0.0002731236,0.000630172,0.0002905694,0.0003097647,0.0009425607,0.0009128989,0.0003203334,0.0005626619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006146489,"about_ca_system_score_gemma":0.0003922883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001024328,"about_ca_topic_score_gemma":0.00186584,"domain_scores_codex":[0.9963007,0.001745707,0.0003398019,0.0003088988,0.001117508,0.0001873802],"domain_scores_gemma":[0.9922001,0.004424768,0.0007873395,0.0003233218,0.001995729,0.0002686823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01718231,0.01280954,0.3542339,0.007985361,0.0008457088,0.0009996147,0.0102636,0.007406178,0.1392381,0.0007824673,0.005192424,0.4430609],"study_design_scores_gemma":[0.001670657,0.1218783,0.7223397,0.0011394,0.001552179,0.001188048,0.01022364,0.02206035,0.1026693,0.0007622288,0.01423571,0.0002805239],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928301,0.0003009985,0.003983667,0.00009485546,0.00004145209,0.0009881575,0.0002544324,0.000115384,0.001391025],"genre_scores_gemma":[0.9712856,0.0003538808,0.02566521,0.0001201314,0.0000234545,0.0007488871,0.0004999675,0.00002149611,0.001281391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005181846,"threshold_uncertainty_score":0.02740455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.161317897713558,"score_gpt":0.4302358180431693,"score_spread":0.2689179203296113,"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."}}