{"id":"W2023090989","doi":"10.1111/j.1748-7692.2007.00171.x","title":"Using form analysis techniques to improve photogrammetric mass‐estimation methods","year":2007,"lang":"en","type":"article","venue":"Marine Mammal Science","topic":"Morphological variations and asymmetry","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Science Foundation","keywords":"Photogrammetry; Covariate; Fourier transform; Range (aeronautics); Fourier analysis; Mathematics; Fourier series; Statistics; Computer science; Artificial intelligence; Mathematical analysis; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005660428,0.0001400275,0.0002463676,0.001312247,0.0002639352,0.000138809,0.0004094728,0.00006755234,0.0002267978],"category_scores_gemma":[0.002041127,0.0001101055,0.0001089209,0.01047417,0.0001053628,0.0002190069,0.0003852305,0.0001199851,0.000007887289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000220202,"about_ca_system_score_gemma":0.00004038532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005400148,"about_ca_topic_score_gemma":0.00004953139,"domain_scores_codex":[0.9982369,0.00003575252,0.000386748,0.0004119747,0.0004475622,0.0004810423],"domain_scores_gemma":[0.9987304,0.0003428392,0.0001564734,0.0003864912,0.0001797803,0.0002040098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001640058,0.0001261791,0.009588469,0.00001850792,0.0000419328,0.00001014359,0.00004863367,0.00007709928,0.1440128,0.04208576,0.00004164124,0.8039324],"study_design_scores_gemma":[0.000306712,0.0004105598,0.08689352,0.00001632458,0.0006342937,0.00002180749,0.0001552555,0.2660052,0.4846302,0.1579042,0.002126624,0.0008952754],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08527679,0.000001426189,0.9009877,0.00005837609,0.0000722867,0.0002906744,0.000002444978,0.0001213996,0.01318886],"genre_scores_gemma":[0.3603505,3.688246e-7,0.6393554,0.0000837926,0.00002834668,0.000008444204,0.000001397529,0.000005161024,0.0001666085],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8030372,"threshold_uncertainty_score":0.503249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06742913840903882,"score_gpt":0.4136762352636051,"score_spread":0.3462470968545663,"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."}}