{"id":"W7165334422","doi":"","title":"Archéologie de Gitanyow, Cranberry Junction - 2020 - Observatoire côtier aéroporté","year":2021,"lang":"","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Orthophoto; Point cloud; Terrain; Hyperspectral imaging; GNSS applications; Lidar; Inertial measurement unit; Geomatics; Aerial survey; Thematic map","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007514854,0.00148853,0.0007059527,0.002043776,0.001849012,0.003745511,0.0006850995,0.0007634916,0.09356932],"category_scores_gemma":[0.0009902616,0.000567439,0.000401664,0.002436506,0.0005872328,0.0008185203,0.001653989,0.002383099,0.02221465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007746768,"about_ca_system_score_gemma":0.008216969,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5422378,"about_ca_topic_score_gemma":0.692959,"domain_scores_codex":[0.9991441,0.00007932294,0.00002718436,0.0002116816,0.0003650703,0.000172671],"domain_scores_gemma":[0.9995449,0.00005201806,0.00004057875,0.00005568708,0.0001324443,0.000174172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00083715,0.0002242731,0.04342779,0.001379564,0.0001729167,0.003594405,0.002749827,0.002981856,0.02331425,0.03385692,0.2997617,0.5876994],"study_design_scores_gemma":[0.00003050865,0.00002530073,0.06942858,0.0001916471,0.000007678776,0.0004932875,0.0005779624,0.00032258,0.001588844,0.0003596033,0.9269483,0.00002573993],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.2053238,0.05365015,0.01025654,0.00480661,0.002055999,0.0007542822,0.06613839,0.003019407,0.6539949],"genre_scores_gemma":[0.1502563,0.0121127,0.02163319,0.0003231958,0.0001354919,0.0003515879,0.02074802,0.001482883,0.7929567],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.4577622,"threshold_uncertainty_score":0.9209162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1497197665155638,"score_gpt":0.3459424759551072,"score_spread":0.1962227094395433,"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."}}