{"id":"W2908245524","doi":"10.1007/978-3-030-00105-6_8","title":"Predicting the Interior Conditions in a High Tunnel Greenhouse","year":2018,"lang":"en","type":"book-chapter","venue":"Springer proceedings in energy","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Microclimate; Greenhouse; Environmental science; San Joaquin; Glazing; Wind tunnel; Meteorology; Wind speed; Atmospheric sciences; Geotechnical engineering; Engineering; Soil science; Agronomy; Civil engineering; Geography; Geology; Aerospace engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002763613,0.0003409064,0.0003858821,0.00009098357,0.0001727127,0.0000609736,0.0006922802,0.0006187941,0.001008955],"category_scores_gemma":[0.00005540918,0.0001392709,0.0001147772,0.0001529254,0.0003182862,0.0001215359,0.0003163339,0.0006022339,0.00005715755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009366454,"about_ca_system_score_gemma":0.00001082714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006724754,"about_ca_topic_score_gemma":0.01423923,"domain_scores_codex":[0.9983587,0.000007463484,0.0004594433,0.0005441596,0.0001913813,0.0004388725],"domain_scores_gemma":[0.9994175,0.00009655184,0.0002544376,0.00008369034,0.00009555472,0.00005225696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002689479,0.000195908,0.0548493,0.0001069174,0.0002087924,0.0001319592,0.001221626,0.000005104008,0.05390939,0.8300246,0.004616116,0.05446134],"study_design_scores_gemma":[0.001836253,0.001363589,0.1462135,0.003126709,0.0001910942,0.0001442777,0.001886178,0.0004641731,0.002243948,0.3164667,0.5233906,0.002673075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.926201,0.0003008363,6.399278e-7,0.001552047,0.0002695393,0.0002656597,0.00004547564,0.0003336942,0.07103112],"genre_scores_gemma":[0.9770429,0.0003337116,0.00001618352,0.000484144,0.0004934585,0.0001223565,0.00002103158,0.000009112084,0.02147707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5187744,"threshold_uncertainty_score":0.9999043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267142500486186,"score_gpt":0.1965122552605157,"score_spread":0.1838408302556538,"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."}}