{"id":"W2087915639","doi":"10.3138/carto.47.4.1504","title":"Land-Use Change in Portugal, 1990–2006: Main Processes and Underlying Factors","year":2012,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Abandonment (legal); Land use, land-use change and forestry; Urbanization; Land use; Spatial change; Enforcement; Land development; Geography; Agricultural land; Agriculture; Driving factors; Software deployment; Natural resource economics; Economic geography; Environmental resource management; Physical geography; Environmental science; Economics; Economic growth; Ecology; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.000635497,0.0001269923,0.0001040564,0.0003060391,0.0003081491,0.000363389,0.0001568631,0.00007229635,0.00005228361],"category_scores_gemma":[0.00007269069,0.00008403156,0.00004777349,0.000372074,0.00003985281,0.003552106,0.00007033495,0.0001015226,0.00000299168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002551904,"about_ca_system_score_gemma":0.000009088104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008490946,"about_ca_topic_score_gemma":0.001723974,"domain_scores_codex":[0.9989676,0.00003569903,0.0003578003,0.00008491815,0.0003221685,0.000231786],"domain_scores_gemma":[0.9994285,0.00009228673,0.0002354594,0.0000638337,0.00007461559,0.0001052936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002685556,0.00002191747,0.9945815,0.00003038133,0.00002450521,3.26262e-7,0.002563947,0.00004654851,0.000006548281,0.0005918368,0.0001002029,0.00200545],"study_design_scores_gemma":[0.000705965,0.00005209938,0.9612864,0.00007695446,0.00002941495,0.00009709581,0.00115094,0.003217637,0.00001679776,0.0008279442,0.03234433,0.000194428],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975357,0.0002678516,0.0007242424,0.0005317779,0.0004961172,0.0003169492,0.0000352242,0.00001939207,0.00007271492],"genre_scores_gemma":[0.9972258,0.001590439,0.00004155751,0.0008681156,0.00009150496,0.00003813817,0.0001326867,0.000006677092,0.000005039411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03329509,"threshold_uncertainty_score":0.3504169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03486592676796475,"score_gpt":0.2893384051394122,"score_spread":0.2544724783714474,"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."}}