{"id":"W7070584316","doi":"","title":"Planificación de trayectorias bi-objetivo en robótica aérea para agricultura de precisión","year":2011,"lang":"es","type":"article","venue":"UPM Digital Archive (Technical University of Madrid)","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Subject (documents); Focus (optics); Quarter (Canadian coin); Term (time)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002603868,0.000485671,0.0006242057,0.00006215871,0.0003601063,0.0001395277,0.001346513,0.0004691092,0.0005169507],"category_scores_gemma":[0.0001799967,0.0002519168,0.0006230387,0.0005427709,0.0006514855,0.0004928971,0.0005467161,0.0005977345,0.0002087086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001500416,"about_ca_system_score_gemma":0.00007320633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007856871,"about_ca_topic_score_gemma":0.0004575854,"domain_scores_codex":[0.9973003,0.0002269048,0.0004055038,0.0007473363,0.0004397251,0.0008801973],"domain_scores_gemma":[0.9980029,0.0008166658,0.0002774356,0.0002152748,0.0001172957,0.0005703602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003500528,0.007913276,0.2138868,0.000297994,0.001002389,0.001260929,0.007575666,0.00003693401,0.5619716,0.05693509,0.08211468,0.06350406],"study_design_scores_gemma":[0.000496501,0.001198207,0.9252034,0.000205859,0.0001772056,0.0001139533,0.001586874,0.00001150442,0.004680056,0.004666948,0.0609661,0.0006933502],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.919701,0.00008467864,0.0006907583,0.001041812,0.0001396019,0.0005434196,0.001213367,0.0002901581,0.07629514],"genre_scores_gemma":[0.9961422,0.0003965434,0.00154289,0.00007412138,0.000396415,0.000001594583,0.0002120653,0.000005799769,0.001228343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7113166,"threshold_uncertainty_score":0.9999933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850161160023639,"score_gpt":0.1895563563533387,"score_spread":0.1710547447531023,"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."}}