{"id":"W4296079691","doi":"10.29173/mocs277","title":"Hindering factors to the utilisation of UAVs for construction projects in South Africa","year":2022,"lang":"en","type":"article","venue":"Modular and Offsite Construction (MOC) Summit Proceedings","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Drone; Software deployment; Construction industry; Integrated project delivery; Investment (military); Business; Construction engineering; Engineering management; Construction management; Engineering; Process management; Civil engineering; Political science; Politics","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":[0.000475073,0.0001441423,0.0003057988,0.0005019527,0.0003792313,0.00007111197,0.0001254819,0.00007682826,0.00009610089],"category_scores_gemma":[0.00008172366,0.0001452755,0.00009083965,0.0007277576,0.00007881795,0.0002615972,0.00007567019,0.0001857052,0.000002052255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001069889,"about_ca_system_score_gemma":0.00001784616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004387807,"about_ca_topic_score_gemma":0.00001091184,"domain_scores_codex":[0.9987429,0.000009831775,0.0005549782,0.0004005278,0.00008674923,0.0002050536],"domain_scores_gemma":[0.999387,0.00002344194,0.0003474737,0.0001067495,0.00008238284,0.00005292557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006594647,0.00004793139,0.8884559,0.00006656619,0.00007893014,2.621533e-7,0.009908763,0.001326333,0.0002907676,0.09004346,0.0001507166,0.009564454],"study_design_scores_gemma":[0.005356679,0.001234451,0.4418362,0.0001259948,0.0002778099,0.00005563826,0.1985666,0.07459787,0.01144438,0.0333889,0.2307672,0.002348323],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913623,0.0001835922,0.006232236,0.0003405145,0.0003143286,0.0004213822,0.0001588503,0.0000252182,0.0009616307],"genre_scores_gemma":[0.9983155,0.000008007632,0.001251509,0.00002752326,0.00006375164,0.0001239882,0.00002749761,0.00001426141,0.000167952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4466197,"threshold_uncertainty_score":0.5924163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04714594478015876,"score_gpt":0.2111585434556014,"score_spread":0.1640125986754426,"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."}}