{"id":"W2060417608","doi":"10.1139/l10-027","title":"Application of partial cross-section precast system to save the Amazon forest","year":2010,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Construction Engineering and Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Precast concrete; Formwork; Structural system; Section (typography); Structural engineering; Civil engineering; Engineering; Process (computing); Cross section (physics); Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000271151,0.0001247407,0.0001704541,0.0002686068,0.00005630913,0.0000444229,0.0001945917,0.0000897826,0.00001930426],"category_scores_gemma":[0.00007137047,0.0001131476,0.00008459494,0.000266778,0.00002483026,0.0001117938,0.000005560897,0.0003927892,0.000004007621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001298839,"about_ca_system_score_gemma":0.00009253706,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000371512,"about_ca_topic_score_gemma":0.030159,"domain_scores_codex":[0.9991804,0.000005461495,0.0003851326,0.00007325638,0.0001259905,0.0002297654],"domain_scores_gemma":[0.999231,0.00003861356,0.00006455041,0.0002014052,0.0001324511,0.0003319174],"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":[0.000002764832,0.000001095193,0.003499125,0.00007510895,0.00002904179,0.000003606329,0.0001639949,0.983484,0.009448558,0.001368593,0.00009057749,0.001833591],"study_design_scores_gemma":[0.0003725317,0.00005946183,0.08704161,0.0001678771,0.00004174483,0.0007614038,0.0001002328,0.8338443,0.004575583,0.00001288235,0.07269786,0.0003245071],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6716439,0.0001163229,0.3224743,0.0000553566,0.004610961,0.0001515037,0.00001610215,0.00008543492,0.000846172],"genre_scores_gemma":[0.9988824,0.000002062237,0.0003496756,0.000002912887,0.0007117807,0.000008821073,0.00000118648,0.00003221295,0.00000892273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3272386,"threshold_uncertainty_score":0.9875381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00382178426877456,"score_gpt":0.1761176290044481,"score_spread":0.1722958447356736,"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."}}