{"id":"W4230849978","doi":"10.1126/science.303.5664.1589a","title":"IMAGES: Homing In on the Range","year":2004,"lang":"en","type":"article","venue":"Science","topic":"Rangeland and Wildlife Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Homing (biology); Range (aeronautics); Geology; Geography; Computer science; Artificial intelligence; Computer vision; Engineering; Aerospace engineering; Geophysics","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":[0.0001058584,0.0006800853,0.0002501433,0.0006423665,0.0008805412,0.0008737635,0.0003670592,0.0008418052,0.2634237],"category_scores_gemma":[0.0004324024,0.0002389865,0.0003673412,0.0004982805,0.0002236773,0.0009575622,0.0009799541,0.001279353,0.05045511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002368838,"about_ca_system_score_gemma":0.0002149652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008539085,"about_ca_topic_score_gemma":0.03246108,"domain_scores_codex":[0.9999478,0.000006046321,0.000001210547,0.00001095376,0.0000150802,0.00001893255],"domain_scores_gemma":[0.9998479,0.00002475859,0.000006225813,0.00002175701,0.00004367428,0.00005575301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001304181,0.00003108138,0.001221205,0.00007254533,0.000009883761,0.0003386364,0.0003145491,0.0002534434,0.001746016,0.0008503377,0.9619023,0.03312954],"study_design_scores_gemma":[0.00005290321,0.00006025918,0.01926121,0.000181399,0.00002125242,0.0007947941,0.001448611,0.001256309,0.001161723,0.001872996,0.9738542,0.00003421517],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02970293,0.00112535,0.01356053,0.007506864,0.007251394,0.0004100125,0.1104721,0.01425228,0.8157185],"genre_scores_gemma":[0.22465,0.002005067,0.05435855,0.006327707,0.001760855,0.0004122785,0.1037325,0.006775547,0.5999776],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2634237,"threshold_uncertainty_score":0.8812399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009404985690388907,"score_gpt":0.2140083345979792,"score_spread":0.2046033489075903,"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."}}