{"id":"W4408419647","doi":"10.1007/s10113-025-02384-y","title":"Building capacities for adaptation planning: moving from needs assessment to action with a multilevel approach","year":2025,"lang":"en","type":"article","venue":"Regional Environmental Change","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Adaptation (eye); Climate change adaptation; Nature Conservation; Action (physics); Multilevel model; Environmental planning; Environmental resource management; Climate change; Environmental science; Computer science; Psychology; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007337543,0.0001208573,0.00009935261,0.0000278158,0.0002805429,0.00005161172,0.00008877488,0.00005735602,0.00003915077],"category_scores_gemma":[0.000004557716,0.00004911856,0.00003582293,0.0001819386,0.00003520787,0.0003261038,0.00003333137,0.00007632133,0.000001986706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001130805,"about_ca_system_score_gemma":0.000003577777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003926229,"about_ca_topic_score_gemma":0.00003409393,"domain_scores_codex":[0.9993443,0.00002340333,0.0001155124,0.0002096642,0.0001615461,0.0001455835],"domain_scores_gemma":[0.9996548,0.0001808081,0.00008294812,0.00003030142,0.00001230271,0.00003886536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005437165,0.000577656,0.01356781,0.00004711986,0.0002177099,0.000002299092,0.006186763,0.001896641,0.6994947,0.01221584,0.002779305,0.2624704],"study_design_scores_gemma":[0.0005721481,0.0005304348,0.7582691,0.0001653556,0.00007834619,0.000008653119,0.0754912,0.01519369,0.002684118,0.0009560669,0.1454924,0.0005585261],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883453,0.0000877063,0.008314275,0.002222734,0.00005576893,0.0005101237,0.0001094915,0.00003056938,0.0003240715],"genre_scores_gemma":[0.9811928,0.00001347146,0.01646441,0.0007564742,0.0002676956,0.0003869898,0.0005371133,0.000001141877,0.0003798555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7447013,"threshold_uncertainty_score":0.2157738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.185696038919987,"score_gpt":0.3106309001625452,"score_spread":0.1249348612425583,"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."}}