{"id":"W2765951767","doi":"10.1007/978-3-319-65993-0_5","title":"Automated Extraction of Movement Rationales for Building Agent-Based Models: Example of a Red Colobus Monkey Group","year":2017,"lang":"en","type":"book-chapter","venue":"Advances in geographic information science","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Movement (music); Terrain; Computer science; Field (mathematics); Geography; Tracking (education); Artificial intelligence; Data science; Cartography; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004564806,0.0007504309,0.0003885584,0.0009358106,0.0006818827,0.00112752,0.0009740448,0.000898743,0.005764694],"category_scores_gemma":[0.001678043,0.000341979,0.0008874472,0.0008328537,0.0002953669,0.0008271455,0.0007875988,0.0007752251,0.001616309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004443912,"about_ca_system_score_gemma":0.0006937446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01181549,"about_ca_topic_score_gemma":0.03222237,"domain_scores_codex":[0.9998623,0.00003871228,0.00001186396,0.00003740611,0.00003829412,0.00001131706],"domain_scores_gemma":[0.9993433,0.0004712608,0.00003493708,0.00007007305,0.00005966098,0.00002076098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002591803,0.0003207563,0.01503123,0.0008280389,0.0002489887,0.003626316,0.002281244,0.2868315,0.02117409,0.05914488,0.03827057,0.5719832],"study_design_scores_gemma":[0.00002911127,0.00003428381,0.002297034,0.00010195,0.00007376383,0.0004480921,0.0003098765,0.923589,0.005626441,0.0258144,0.04165009,0.00002589731],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1249804,0.001310385,0.8311669,0.001376572,0.000182779,0.0003107578,0.006121983,0.008496643,0.02605346],"genre_scores_gemma":[0.2453759,0.0005831082,0.7369239,0.00009806351,0.00002396938,0.0001417551,0.005992771,0.0007142354,0.01014632],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01181549,"threshold_uncertainty_score":0.02349341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02283885249571527,"score_gpt":0.2714519395198022,"score_spread":0.2486130870240869,"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."}}