{"id":"W4415762554","doi":"10.1111/2041-210x.70188","title":"Time‐lapse cameras bridge the gap between remote sensing and in situ observations of tundra phenology","year":2025,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Research Committee, Aristotle University of Thessaloniki; Natural Environment Research Council; Knut och Alice Wallenbergs Stiftelse; Gatsby Charitable Foundation","keywords":"Tundra; Phenology; Arctic; Climate change; Ecosystem; Vegetation (pathology); Satellite; Bay","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001032582,0.00006518731,0.0001884952,0.0001400078,0.0001073088,0.000006124453,0.00005020867,0.0001252938,0.00005362106],"category_scores_gemma":[0.0002157145,0.00005341084,0.00001317415,0.0002709463,0.0002568958,0.00006202699,0.00002319531,0.0001528574,0.000003232937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009878266,"about_ca_system_score_gemma":0.00002843727,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005941374,"about_ca_topic_score_gemma":0.09364113,"domain_scores_codex":[0.9988879,0.0005734633,0.0002009302,0.0001478524,0.00002589493,0.0001639817],"domain_scores_gemma":[0.9985693,0.00125762,0.00005100467,0.00008765327,0.00001758489,0.00001688243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002263977,0.000003278104,0.9653575,0.00001667294,0.000007030954,0.000001707025,0.0004930066,0.00007402247,0.001838382,0.00004226029,0.00006668741,0.03207678],"study_design_scores_gemma":[0.0001960816,0.00003143739,0.9726472,0.00001746494,0.00001570787,0.000006279603,0.0001966641,0.01708593,0.00005356026,0.009449731,0.0002523237,0.00004762198],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941849,0.001246305,0.002276421,0.001355429,0.0001588336,0.0001165746,0.00005649607,0.000005824982,0.0005992235],"genre_scores_gemma":[0.9884924,0.0002444003,0.01078897,0.0002100107,0.00003075478,2.359456e-7,0.000100821,0.000001254182,0.0001311811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08769976,"threshold_uncertainty_score":0.9228976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09060117710571647,"score_gpt":0.343836711410286,"score_spread":0.2532355343045695,"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."}}