{"id":"W2953527716","doi":"10.29173/mocs103","title":"Transfer Learning Enabled Process Recognition for Module Installation of High-rise Modular Buildings","year":2019,"lang":"en","type":"article","venue":"Modular and Offsite Construction (MOC) Summit Proceedings","topic":"BIM and Construction Integration","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Modular design; Process (computing); Automation; Computer science; Engineering; Convolutional neural network; Building automation; Embedded system; Software engineering; Systems engineering; Artificial intelligence; Operating system; Mechanical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003941054,0.0006229702,0.000311157,0.0007432357,0.0001533763,0.000552777,0.0006557347,0.0005383844,0.0009345119],"category_scores_gemma":[0.0007489017,0.00027549,0.0007203089,0.0005739098,0.0002474067,0.000924463,0.0004490074,0.0004575703,0.0003872169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007561417,"about_ca_system_score_gemma":0.0005513481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006310919,"about_ca_topic_score_gemma":0.006252552,"domain_scores_codex":[0.999755,0.00002430864,0.00001176775,0.00006939233,0.0001053252,0.00003417352],"domain_scores_gemma":[0.9998152,0.00004324513,0.00003627131,0.00002168968,0.00007584121,0.000007902375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001664682,0.0001831299,0.006400959,0.000449783,0.00009890201,0.0004164397,0.0001607652,0.3583369,0.04937719,0.002816764,0.002184158,0.5794085],"study_design_scores_gemma":[0.000002922613,0.00006009352,0.003318963,0.00001733442,0.00003795216,0.00009142298,0.00002508006,0.9740424,0.01957227,0.0008627919,0.001955183,0.00001363543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1461283,0.001949111,0.8428632,0.0001906448,0.0001016454,0.00007614851,0.0002070881,0.002573862,0.005910053],"genre_scores_gemma":[0.9202591,0.001492002,0.07361082,0.00006595134,0.00002509637,0.00005707569,0.0004466295,0.00005302504,0.003990317],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006310919,"threshold_uncertainty_score":0.01254833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006434172699105438,"score_gpt":0.1866436558455424,"score_spread":0.180209483146437,"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."}}