{"id":"W3024054255","doi":"10.4095/326066","title":"2016 unmanned aerial vehicle study at Mer Bleue, Ontario","year":2020,"lang":"en","type":"report","venue":"","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Astrobiology; Environmental science; Geology; Remote sensing; Geography; Oceanography; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002356197,0.00024678,0.0002801362,0.0007596423,0.002046474,0.0007588957,0.0004065727,0.0003288205,0.01012232],"category_scores_gemma":[0.0004937909,0.000206782,0.0002002314,0.00133634,0.0005677038,0.0004622767,0.0007125747,0.0002748991,0.002734601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007971861,"about_ca_system_score_gemma":0.01281081,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9428488,"about_ca_topic_score_gemma":0.9865977,"domain_scores_codex":[0.9996355,0.00001318109,0.0000073376,0.00005450271,0.0002105321,0.00007889386],"domain_scores_gemma":[0.9995471,0.00001779642,0.00003365054,0.00002928133,0.0002976155,0.00007460929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001275144,0.0003890738,0.5812429,0.000431845,0.0001544425,0.002672438,0.01091601,0.005602419,0.02264436,0.00395433,0.2485752,0.1221417],"study_design_scores_gemma":[0.00003148906,0.000115559,0.8187577,0.00005061518,0.00001639062,0.0001049283,0.005695485,0.001461667,0.00208381,0.0002688494,0.1713921,0.00002155369],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7377256,0.0005241376,0.001308595,0.001601354,0.000216279,0.000606473,0.06769466,0.0001985145,0.1901246],"genre_scores_gemma":[0.6821509,0.0007980358,0.001575162,0.0001502193,0.00004042542,0.0001743409,0.02466255,0.0001085688,0.2903398],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0571512,"threshold_uncertainty_score":0.1149755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06208298134093475,"score_gpt":0.2519343910439051,"score_spread":0.1898514097029704,"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."}}