{"id":"W7011212306","doi":"","title":"Mapping Spinach Yield Using UAV-Based Multispectral Imagery Data","year":2023,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Economic and Social Issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Multispectral image; Spinach; Yield (engineering); Reflectivity; Multispectral pattern recognition","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.00008738368,0.0001784082,0.0001473045,0.0004663735,0.0001933245,0.0004164343,0.0001285164,0.0001150482,0.0009387446],"category_scores_gemma":[0.0001481221,0.0000973214,0.000190651,0.000824743,0.00004894643,0.0002834312,0.0001442409,0.0001485053,0.0002626111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002653155,"about_ca_system_score_gemma":0.0002768333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02320214,"about_ca_topic_score_gemma":0.05549078,"domain_scores_codex":[0.9999574,0.000002281574,0.000001192558,0.00001577657,0.00001415312,0.00000908159],"domain_scores_gemma":[0.9999328,0.000007988569,0.00000687084,0.000004928087,0.00003908733,0.000008253221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000285112,0.0002837348,0.3208911,0.0001381413,0.0001477712,0.0003398644,0.0004681393,0.03080588,0.1855497,0.0005249308,0.004697843,0.4558678],"study_design_scores_gemma":[0.00002386862,0.0001277517,0.8390419,0.00001903764,0.0001516539,0.00005446015,0.001765141,0.1338723,0.01954628,0.0003930939,0.004976086,0.00002838029],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911329,0.00008594317,0.004737588,0.00006747166,0.00001299098,0.00001277599,0.0006887795,0.0001479906,0.003113518],"genre_scores_gemma":[0.9925882,0.00011359,0.004432683,0.00001170603,0.000004065677,0.000007592526,0.0009056853,0.00001700662,0.001919532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02320214,"threshold_uncertainty_score":0.04613417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1176746631990538,"score_gpt":0.3450193489251663,"score_spread":0.2273446857261125,"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."}}