{"id":"W2347030253","doi":"10.1144/jgs2015-086","title":"Categorization of shell fragments provides a proxy for environmental energy and predation intensity","year":2016,"lang":"en","type":"article","venue":"Journal of the Geological Society","topic":"Cephalopods and Marine Biology","field":"Agricultural and Biological Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Geographic Society","keywords":"Categorization; Geology; Proxy (statistics); Predation; Paleontology; Artificial intelligence; Statistics; Computer science; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003165081,0.0003458815,0.0002596945,0.002739937,0.0006275743,0.0007957701,0.00045503,0.0002923872,0.001762535],"category_scores_gemma":[0.001532019,0.0002083431,0.0002044623,0.001493717,0.0008071524,0.0003393893,0.0008004801,0.0002570045,0.0002634111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007546501,"about_ca_system_score_gemma":0.0003433172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07753012,"about_ca_topic_score_gemma":0.260821,"domain_scores_codex":[0.9996035,0.00004245106,0.00004552992,0.00009621749,0.0001399844,0.00007239393],"domain_scores_gemma":[0.9985867,0.0001918523,0.0006812194,0.0001082391,0.0002533973,0.0001785518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007571114,0.00001299779,0.9876112,0.00002993136,0.00005441071,0.00007681912,0.0004948676,0.0002144499,0.005350916,0.00005528627,0.0001052767,0.005918118],"study_design_scores_gemma":[5.736106e-7,0.000009036774,0.9994947,0.000002933397,0.000003314648,0.00004689444,0.000197225,0.00009296548,0.00006777374,0.00001601981,0.00006711818,0.000001580551],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979874,0.0001036582,0.0004130182,0.000009370998,0.00000116946,0.0000148506,0.0004649229,0.000008379833,0.0009971714],"genre_scores_gemma":[0.9981225,0.00005860891,0.0009074925,0.000007395388,0.000001792396,0.0000138768,0.0005837627,0.000003412736,0.0003011534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07753012,"threshold_uncertainty_score":0.1541577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00877007920051301,"score_gpt":0.1829277665345936,"score_spread":0.1741576873340806,"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."}}