{"id":"W4386815053","doi":"10.52842/conf.ecaade.2023.2.001","title":"eCAADe 2023 Digital Design Reconsidered - Volume 2","year":2023,"lang":"en","type":"article","venue":"eCAADe proceedings","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universität Innsbruck; Universität Stuttgart; Istanbul Teknik Üniversitesi; Universidade do Porto; Universidade de São Paulo; Technische Universität Wien; Bauhaus-Universität Weimar; Nanchang University; Technische Universität München; KU Leuven; Università degli Studi di Torino; Universidad de Chile; Carnegie Mellon University; National University of Singapore; Eidgenössische Technische Hochschule Zürich; Chalmers Tekniska Högskola; Hague University of Applied Sciences; University of Texas at San Antonio; TU Graz, Internationale Beziehungen und Mobilitätsprogramme; Université Laval; Texas Tech University","keywords":"Volume (thermodynamics); Computer science; Environmental science; Physics; Thermodynamics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001422764,0.0002102815,0.0001810313,0.0002129914,0.0001004094,0.0003243638,0.0001824956,0.0001263113,0.0002454456],"category_scores_gemma":[0.00009911316,0.0002219923,0.00005308403,0.0005039782,0.00002626188,0.0006769433,0.00005033491,0.0001791898,0.00132268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005064256,"about_ca_system_score_gemma":0.00001450253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000236578,"about_ca_topic_score_gemma":3.21455e-7,"domain_scores_codex":[0.9988763,0.000001559722,0.0002428921,0.0002679997,0.000187471,0.0004238199],"domain_scores_gemma":[0.9996651,0.00002945169,0.00004077637,0.00008642603,0.00006262679,0.0001156496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000385453,0.00003788543,0.002453679,0.0009187355,0.0001477951,0.00002852534,0.002641668,0.2443737,0.002337329,0.0004229063,0.7183702,0.028229],"study_design_scores_gemma":[0.0007735328,0.0001037064,0.004557217,0.0001729844,0.00003985425,0.00004232882,0.0005065647,0.82866,0.03295453,0.006046381,0.1249555,0.00118747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6032254,0.001252704,0.1104334,0.00534826,0.004399092,0.002918859,0.0001622728,0.02976898,0.242491],"genre_scores_gemma":[0.9872851,0.000154842,0.003307936,0.0000485096,0.0002734624,0.00008380959,0.00003762963,0.0001069516,0.008701753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5934147,"threshold_uncertainty_score":0.9994549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02016539997110923,"score_gpt":0.1978999164998222,"score_spread":0.1777345165287129,"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."}}