{"id":"W4387404806","doi":"10.1007/978-3-031-36922-3_42","title":"From DfMA to DfR: Exploring a Digital and Physical Technological Stack to Enable Digital Timber for SMEs","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in mechanical engineering","topic":"Architecture and Computational Design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Factory (object-oriented programming); Engineering; Manufacturing engineering; Carpentry; Building information modeling; Productivity; Systems engineering; Engineering management; Computer science; Operations management; Civil 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006118527,0.0005688465,0.0006216682,0.0003274578,0.0000347565,0.0001718416,0.0002723044,0.0003808345,0.000009678641],"category_scores_gemma":[0.0004368364,0.0005518221,0.0001605135,0.000170411,0.00001743019,0.0001407637,0.000248231,0.000691843,0.00008789221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001195781,"about_ca_system_score_gemma":0.00001348941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000146039,"about_ca_topic_score_gemma":0.000002808684,"domain_scores_codex":[0.9982506,0.000002674879,0.0003358384,0.0006215391,0.0002844887,0.0005048458],"domain_scores_gemma":[0.9984423,0.001011701,0.00002214581,0.0002698576,0.00003197144,0.0002220564],"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":[0.0000418848,0.00001144954,5.016348e-7,0.00009815241,0.0001092584,0.00004170198,0.0002292545,0.9043514,0.002251321,0.01150915,0.0000820979,0.08127382],"study_design_scores_gemma":[0.000572222,0.0005470974,0.000007701873,0.001121384,0.00007369722,0.00001822324,0.00001659755,0.532196,0.01373188,0.4116338,0.03784061,0.002240701],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007323799,0.00009542061,0.9889774,0.0002080354,0.0002840282,0.0007061229,0.0003465537,0.00117027,0.0008883438],"genre_scores_gemma":[0.9758179,0.00001749226,0.02137067,0.0001011214,0.001095061,0.0003831123,0.0001395005,0.0003875093,0.0006876646],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9684941,"threshold_uncertainty_score":0.9996933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0219211200937909,"score_gpt":0.2105739449669828,"score_spread":0.1886528248731919,"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."}}