{"id":"W2352634312","doi":"","title":"ECOLOGICAL FOOTPRINT ANALYSIS: CONCEPT, METHOD AND CASES","year":2000,"lang":"en","type":"article","venue":"Advance in Earth Sciences","topic":"Environmental Quality and Pollution","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ecological footprint; Adaptability; Footprint; Measure (data warehouse); Sustainable development; Environmental resource management; Computer science; Ecology; Environmental science; Geography; Data mining; Archaeology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005328176,0.00008442011,0.0001332398,0.00003601663,0.0001687209,0.00002367051,0.0001414338,0.00003522592,0.004854984],"category_scores_gemma":[0.00003824846,0.00006845802,0.00003486375,0.0006295457,0.0009116982,0.0003046463,0.00005853343,0.00007653991,0.0001180655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001846594,"about_ca_system_score_gemma":0.000003251652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000412435,"about_ca_topic_score_gemma":0.00146036,"domain_scores_codex":[0.9988953,0.0001301256,0.0001644423,0.0003664673,0.0002100791,0.0002335758],"domain_scores_gemma":[0.9995626,0.0002333371,0.000035519,0.0001020534,6.168847e-7,0.00006582633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001747787,0.0001146676,0.5105054,0.00000160864,0.000008832219,0.0000238998,0.0004554873,0.3385323,0.0009792047,0.0009448882,0.000007666313,0.1484085],"study_design_scores_gemma":[0.0001134563,0.0001601538,0.9863529,0.000003408992,0.00001432535,0.00001502352,0.0001654259,0.004005696,0.0008351955,0.001993957,0.006208928,0.0001314816],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905313,0.0001666399,0.0007296852,0.0003324698,0.0000204905,0.00008686326,0.000003779259,0.00001504099,0.008113714],"genre_scores_gemma":[0.9853424,0.0002250362,0.01362001,0.0003730766,0.000008116531,0.000007214642,9.434082e-7,0.000001479536,0.0004217341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4758475,"threshold_uncertainty_score":0.9960547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02086516009906661,"score_gpt":0.3162952382945763,"score_spread":0.2954300781955097,"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."}}