{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001720574,0.0002124449,0.0001576729,0.0009080467,0.001231351,0.001559541,0.0003449821,0.0003243242,0.003207364],"category_scores_gemma":[0.008320171,0.0002445954,0.0001200765,0.001399659,0.0007755728,0.0007919937,0.001076947,0.0004375738,0.0001918909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001668697,"about_ca_system_score_gemma":0.004327759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02041454,"about_ca_topic_score_gemma":0.03967442,"domain_scores_codex":[0.9981607,0.0007636244,0.0001357116,0.00008942198,0.0003115525,0.0005390123],"domain_scores_gemma":[0.9918133,0.003251918,0.003252472,0.0001468116,0.0006355669,0.0008999104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002120639,0.000359003,0.7857327,0.00116264,0.00005620403,0.006657661,0.09174202,0.00163449,0.01007769,0.007411605,0.001784949,0.09316894],"study_design_scores_gemma":[0.000008284906,0.0002350347,0.8042013,0.0006847029,0.00002812212,0.001194853,0.1715551,0.001065003,0.001015933,0.0005864014,0.01939267,0.00003258952],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967983,0.0001937741,0.000249988,0.0005123261,0.000003383493,0.00002260929,0.00002428956,0.000002111959,0.002193302],"genre_scores_gemma":[0.9987189,0.0004262091,0.0002532158,0.00002525002,0.000001881623,0.00001360056,0.000009750081,0.000001724764,0.0005494629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02041454,"threshold_uncertainty_score":0.04059142,"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."}}